WO2017098931A1 - 超音波診断装置、超音波診断装置の作動方法および超音波診断装置の作動プログラム - Google Patents
超音波診断装置、超音波診断装置の作動方法および超音波診断装置の作動プログラム Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5269—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving detection or reduction of artifacts
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
- G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
- G01S7/52023—Details of receivers
- G01S7/52036—Details of receivers using analysis of echo signal for target characterisation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
- A61B8/0833—Detecting organic movements or changes, e.g. tumours, cysts, swellings involving detecting or locating foreign bodies or organic structures
- A61B8/085—Detecting organic movements or changes, e.g. tumours, cysts, swellings involving detecting or locating foreign bodies or organic structures for locating body or organic structures, e.g. tumours, calculi, blood vessels, nodules
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/12—Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5207—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of raw data to produce diagnostic data, e.g. for generating an image
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
- A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/54—Control of the diagnostic device
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
- G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
- G01S7/52053—Display arrangements
- G01S7/52057—Cathode ray tube displays
- G01S7/52071—Multicolour displays; using colour coding; Optimising colour or information content in displays, e.g. parametric imaging
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/46—Ultrasonic, sonic or infrasonic diagnostic devices with special arrangements for interfacing with the operator or the patient
- A61B8/461—Displaying means of special interest
- A61B8/463—Displaying means of special interest characterised by displaying multiple images or images and diagnostic data on one display
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/58—Testing, adjusting or calibrating the diagnostic device
- A61B8/587—Calibration phantoms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10132—Ultrasound image
Definitions
- the present invention relates to an ultrasonic diagnostic apparatus that observes a tissue to be observed using ultrasonic waves, an operating method of the ultrasonic diagnostic apparatus, and an operating program of the ultrasonic diagnostic apparatus.
- a feature quantity image to which visual information corresponding to the feature quantity, for example, color information is added is generated and displayed.
- An operator such as a doctor diagnoses the tissue properties of the specimen by looking at the displayed feature value image.
- Patent Document 1 does not correspond to a physical quantity such as a diameter or number density of a scatterer included in an observation target because the feature quantity of the frequency spectrum is associated with the structure based on the color information provided according to the feature quantity. Skill was necessary to distinguish the properties. For this reason, there has been a demand for a technique that can easily distinguish tissue properties without requiring skill.
- the present invention has been made in view of the above, and includes an ultrasonic diagnostic apparatus, an operation method of the ultrasonic diagnostic apparatus, and an ultrasonic diagnostic apparatus capable of easily and accurately distinguishing tissue characteristics based on feature amounts.
- the purpose is to provide an operating program.
- an ultrasonic diagnostic apparatus transmits an ultrasonic wave to an observation target and receives an ultrasonic wave back-scattered by the observation target.
- An ultrasound diagnostic apparatus that generates an ultrasound image based on an ultrasound signal acquired by an ultrasound probe including: a feature amount calculation unit that calculates a feature amount based on an ultrasound signal received from the observation target And the relationship derived based on the physical quantity of the reference object whose physical quantity of the scatterer contained is known and the characteristic quantity obtained from the target object, and the characteristic quantity of the observation target calculated by the feature quantity calculation unit And an estimation unit that estimates the physical quantity of the scatterer included in the observation target, and a physical quantity information generation unit that generates an information to be displayed on the display unit, including an estimation result by the estimation unit. It is characterized by .
- the physical quantity contained in the reference object includes at least one of the number density of the scatterers, the size of the scatterers, and the scattering intensity of the scatterers. It is characterized by that.
- the physical quantity includes a scattering intensity of a scatterer contained in the reference object, and the scattering intensity includes an amplitude reflectance and an energy reflectance of the scatterer and the medium. And / or a function thereof.
- the estimation unit includes a scatterer included in the observation target by substituting the feature amount calculated by the feature amount calculation unit into the relational expression as the relationship.
- the physical quantity of is estimated.
- a relational information storage that stores at least one of the relational expression, a coefficient of the relational expression, a constant term of the relational expression, and a table describing the relation
- the estimation unit estimates a physical quantity of the scatterer included in the observation target with reference to the relation information storage unit.
- the ultrasonic diagnostic apparatus is characterized in that, in the above invention, the relational expression is derived by performing multiple regression analysis on at least a part of the physical quantity and the feature quantity.
- the ultrasonic diagnostic apparatus in the above invention, includes the number density of the scatterers and the number density of the scatterers among the physical quantities of the known scatterers, and the number density of the scatterers, and The multiple regression analysis is performed by nonlinearly transforming the scatterer.
- the ultrasonic diagnostic apparatus is characterized in that, in the above invention, the feature amount includes a frequency feature amount calculated based on the ultrasonic signal.
- the ultrasonic diagnostic apparatus is characterized in that, in the above invention, the feature amount includes an attenuation rate calculated based on the ultrasonic signal.
- the ultrasonic diagnostic apparatus is characterized in that, in the above invention, the feature amount includes a speed of sound calculated based on the ultrasonic signal.
- the ultrasonic diagnostic apparatus is characterized in that, in the above-described invention, the physical quantity information generation unit generates image data to which visual information is given according to the physical quantity estimated by the estimation unit.
- the physical quantity information generation unit is configured to display the plurality of physical quantities simultaneously, sequentially, or at different timings. The information displayed on the screen is generated.
- the ultrasonic diagnostic apparatus further includes a variable conversion unit that further performs non-linear conversion on the number density of the scatterers subjected to the non-linear conversion and / or the size of the scatterers. It is characterized by having.
- the ultrasonic diagnostic apparatus further includes an attenuation correction unit that corrects an influence of attenuation in the feature amount calculated based on the ultrasonic signal received from the observation target in the above invention
- the estimation unit includes the inclusion A relationship derived based on the physical quantity of the reference object with a known physical quantity of the scatterer and a value obtained by correcting the influence of attenuation on the feature quantity obtained from the reference object, and the attenuation correction unit A physical quantity of a scatterer included in the observation target is estimated using a value of the feature quantity of the observation target.
- the operation method of the ultrasonic diagnostic apparatus according to the present invention is an ultrasonic wave acquired by an ultrasonic probe including an ultrasonic transducer that transmits ultrasonic waves to an observation target and receives ultrasonic waves back-scattered by the observation target.
- An operation method of an ultrasonic diagnostic apparatus that generates an ultrasonic image based on a signal, wherein a feature amount calculation unit calculates a feature amount based on an ultrasonic signal received from the observation target; and
- the estimation unit includes the relationship derived based on the physical quantity of the reference object whose physical quantity of the scatterer contained is known, and the feature quantity obtained from the reference object, and the observation target calculated by the feature quantity calculation unit
- the operation program of the ultrasonic diagnostic apparatus includes an ultrasonic wave acquired by an ultrasonic probe including an ultrasonic transducer that transmits an ultrasonic wave to an observation target and receives an ultrasonic wave backscattered by the observation target.
- An operation program for an ultrasound diagnostic apparatus that generates an ultrasound image based on a signal, wherein a feature amount calculation unit calculates a feature amount based on an ultrasound signal received from the observation target; and
- the estimation unit includes the relationship derived based on the physical quantity of the target object whose physical quantity of the scatterer contained is known and the characteristic quantity obtained from the reference object, and the observation target calculated by the feature quantity calculation unit.
- An estimation procedure for estimating a physical quantity of a scatterer included in the observation target using a feature quantity, and a physical quantity information generation unit including an estimation result by the estimation unit and generating information to be displayed on a display unit An information generation procedure, characterized in that to be executed by the ultrasonic diagnostic apparatus.
- FIG. 1 is a block diagram showing a configuration of an ultrasonic diagnostic system including an ultrasonic diagnostic apparatus according to Embodiment 1 of the present invention.
- FIG. 2 is a diagram showing the relationship between the reception depth and the amplification factor in the amplification processing performed by the signal amplification unit of the ultrasonic diagnostic apparatus according to Embodiment 1 of the present invention.
- FIG. 3 is a diagram schematically showing the scanning area of the ultrasonic transducer and the B-mode reception data.
- FIG. 4 is a diagram schematically showing a data array in one sound ray of the ultrasonic signal.
- FIG. 5 is a diagram illustrating an example of spectrum data calculated by the frequency analysis unit of the ultrasonic diagnostic apparatus according to Embodiment 1 of the present invention.
- FIG. 1 is a block diagram showing a configuration of an ultrasonic diagnostic system including an ultrasonic diagnostic apparatus according to Embodiment 1 of the present invention.
- FIG. 2 is a diagram showing the relationship between the reception depth and the amplification
- FIG. 6 is a diagram showing a straight line having as a parameter the corrected feature amount corrected by the attenuation correction unit of the ultrasonic diagnostic apparatus according to Embodiment 1 of the present invention.
- FIG. 7 is a diagram illustrating the relationship between the midband fit, the diameter of the scatterers, and the number density, and is a diagram for explaining the regression plane.
- FIG. 8 is a flowchart showing an outline of processing performed by the ultrasound diagnostic apparatus according to Embodiment 1 of the present invention.
- FIG. 9 is a flowchart showing an outline of processing executed by the frequency analysis unit of the ultrasonic diagnostic apparatus according to Embodiment 1 of the present invention.
- FIG. 10 is a diagram schematically showing a display example of the feature amount image in the display device of the ultrasonic diagnostic apparatus according to Embodiment 1 of the present invention.
- FIG. 11 is a block diagram showing a configuration of an ultrasonic diagnostic system including an ultrasonic diagnostic apparatus according to a modification of the first embodiment of the present invention.
- FIG. 12 is a diagram schematically illustrating a display example of the feature amount image in the display device of the ultrasonic diagnostic apparatus according to the modification of the first embodiment of the present invention.
- FIG. 13 is a block diagram showing a configuration of an ultrasonic diagnostic system including the ultrasonic diagnostic apparatus according to Embodiment 3 of the present invention.
- FIG. 14 is a block diagram showing a configuration of an ultrasonic diagnostic system including the ultrasonic diagnostic apparatus according to Embodiment 4 of the present invention.
- FIG. 15 is a diagram for explaining a lookup table stored in the ultrasonic diagnostic apparatus according to Embodiment 4 of the present invention.
- FIG. 1 is a block diagram showing a configuration of an ultrasonic diagnostic system 1 including an ultrasonic diagnostic apparatus 3 according to Embodiment 1 of the present invention.
- the ultrasonic diagnostic system 1 shown in FIG. 1 transmits an ultrasonic wave to an observation target that is an observation target, and receives an ultrasonic wave backscattered by the observation target, and an ultrasonic endoscope.
- 2 includes an ultrasonic diagnostic apparatus 3 that generates an ultrasonic image based on the ultrasonic signal acquired by the apparatus 2 and a display apparatus 4 that displays the ultrasonic image generated by the ultrasonic diagnostic apparatus 3.
- the ultrasonic diagnostic apparatus 3 can connect one ultrasonic endoscope 2 or plural ultrasonic endoscopes 2 at the same time regardless of the same type or different types of the ultrasonic endoscope 2.
- the ultrasonic endoscope 2 functions as an ultrasonic probe.
- a solid arrow indicates transmission of an electric signal related to an image
- a broken arrow indicates transmission of an electric signal related to control.
- the ultrasonic endoscope 2 converts an electrical pulse signal received from the ultrasonic diagnostic apparatus 3 into an ultrasonic pulse (acoustic pulse) and irradiates the observation target at the tip thereof, and backscatters at the observation target. It has an ultrasonic transducer 21 that converts the ultrasonic echo that has been converted into an electrical echo signal that represents a voltage change.
- the ultrasonic endoscope 2 usually has an imaging optical system and an imaging element at the distal end thereof, and the observation target digestive tract (esophagus, stomach, duodenum, large intestine) or respiratory organ (trachea, The gastrointestinal tract and the respiratory tract and surrounding organs (pancreas, gallbladder, bile duct, biliary tract, lymph node, mediastinal organ, blood vessel, etc.) can be imaged.
- the ultrasonic endoscope 2 has a long insertion portion to be observed.
- the insertion unit usually includes a light guide that guides illumination light irradiated onto the observation target during imaging.
- the light guide has a distal end portion reaching the distal end of the insertion portion, and a proximal end portion connected to a light source device that generates illumination light.
- the ultrasonic diagnostic apparatus 3 is electrically connected to the ultrasonic endoscope 2 and transmits a transmission signal (pulse signal) including a high voltage pulse to the ultrasonic transducer 21 based on a predetermined waveform and transmission timing.
- a transmission / reception unit 31 that receives an echo signal, which is an electrical reception signal, from the ultrasonic transducer 21 to generate and output digital data (hereinafter referred to as RF data) of a radio frequency (RF) signal, and a transmission / reception unit
- RF data digital data
- a signal processing unit 32 that generates digital B-mode reception data based on the RF data received from 31, a calculation unit 33 that performs a predetermined calculation on the RF data received from the transmission / reception unit 31, and various image data
- an input unit 3 that receives various types of information and is realized using a user interface such as a keyboard, a mouse, and a touch panel.
- the transmission / reception unit 31 includes a signal amplification unit 311 that amplifies the echo signal.
- the signal amplification unit 311 performs STC (Sensitivity Time Control) correction in which an echo signal having a larger reception depth is amplified with a higher amplification factor.
- FIG. 2 is a diagram illustrating the relationship between the reception depth and the amplification factor in the amplification process performed by the signal amplification unit 311.
- the reception depth z shown in FIG. 2 is an amount calculated based on the elapsed time from the reception start point of the ultrasonic wave. As shown in FIG.
- the amplification factor ⁇ (dB) increases linearly from ⁇ 0 to ⁇ th (> ⁇ 0 ) as the reception depth z increases.
- the amplification factor ⁇ (dB) takes a constant value ⁇ th when the reception depth z is equal to or greater than the threshold value z th .
- the value of the threshold value z th is such a value that the ultrasonic signal received from the observation target is almost attenuated and the noise becomes dominant. More generally, when the reception depth z is smaller than the threshold value z th , the amplification factor ⁇ may increase monotonously as the reception depth z increases.
- the relationship shown in FIG. 2 is stored in the storage unit 37 in advance.
- the transmission / reception unit 31 performs processing such as filtering on both the echo signal amplified by the signal amplification unit 311 and the original echo signal that is not amplified, and then samples at an appropriate sampling frequency (for example, 50 MHz). Discretization (so-called A / D conversion processing) is performed. In this way, the transmission / reception unit 31 generates two RF data, the RF data A discretized from the non-amplified echo signal and the RF data N discretized from the non-amplified echo signal, to the signal processing unit 32 and the calculation unit 33. Output.
- A is an abbreviation for “Amplified”
- N is an abbreviation for “Normal”.
- the transmission / reception unit 31 includes a plurality of beams for beam synthesis corresponding to the plurality of elements.
- a channel circuit is included.
- the frequency band of the pulse signal transmitted by the transmission / reception unit 31 is a wide band that substantially covers the linear response frequency band when the ultrasonic transducer 21 performs electroacoustic conversion of the pulse signal into the ultrasonic pulse.
- various processing frequency bands of the echo signal in the signal amplifying unit 311 are set to a wide band substantially covering the linear response frequency band when the ultrasonic transducer 21 performs acoustoelectric conversion of the ultrasonic echo into the echo signal. Accordingly, it is possible to perform accurate approximation when performing frequency spectrum approximation processing, which will be described later.
- the transmission / reception unit 31 transmits various control signals output from the control unit 36 to the ultrasonic endoscope 2 and receives various types of information including an identification ID from the ultrasonic endoscope 2 to control the control unit. 36 also has a function of transmitting to 36.
- the signal processing unit 32 performs known processing such as bandpass filter, envelope detection, logarithmic conversion, and the like on the RF data A to generate digital B-mode reception data.
- logarithmic conversion the common logarithm of the amount obtained by dividing the RF data A by the reference voltage V c is taken and expressed in decibel values.
- this B-mode reception data the amplitude or intensity of the received signal indicating the intensity of backscattering of the ultrasonic pulse is lined up along the transmission / reception direction (depth direction) of the ultrasonic pulse.
- FIG. 3 is a diagram schematically showing a scanning area of the ultrasonic transducer 21 (hereinafter sometimes simply referred to as a scanning area) and B-mode reception data.
- the ultrasonic transducer 21 represents a path (sound ray) along which the ultrasonic wave reciprocates as a straight line, and represents the B-mode reception data lined up on each sound ray.
- numbers are assigned to the sound lines in order from the start of scanning (right of FIG. 3).
- SR 1 of the first sound line, the second of sound ray SR 2, 3 th sound line SR 3, ⁇ , the k-th sound line is defined as SR k.
- FIG. 3 corresponds to the case where the ultrasonic transducer 21 is a convex transducer.
- the reception depth of the B-mode reception data is indicated as z.
- the signal processing unit 32 outputs the generated B-mode reception data to the B-mode image data generation unit 341 of the image processing unit 34.
- the signal processing unit 32 is realized using a general-purpose processor such as a CPU (Central Processing Unit) or a dedicated integrated circuit that performs a specific function such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). Is done.
- the calculation unit 33 performs a frequency analysis by performing a fast Fourier transform (FFT) on the RF data N generated by the transmission / reception unit 31, and a frequency analysis unit 331 that calculates spectrum data by the frequency analysis unit 331.
- FFT fast Fourier transform
- the single regression analysis unit 332 feature amount calculation unit
- the number density is calculated using a relational expression derived from the number density (hereinafter, the number density is n) and the diameter (hereinafter, the diameter of the scatterer is d) of the scatterer.
- the calculation unit 33 is realized using a CPU (Central Processing Unit), various calculation circuits, and the like.
- the number density of scatterers means the number of scatterers contained per unit volume, and the unit in the present embodiment is [pieces / cm 3 ].
- the unit of the diameter d in this embodiment is [ ⁇ m].
- the logarithm of the number density and the diameter of the scatterer is a common logarithm, and the bottom is 10. Therefore, logn and logd represent the number of decimal digits ⁇ 1 of n and d.
- the frequency analysis unit 331 again samples the RF data N (line data) of each sound ray generated by the transmission / reception unit 31 at predetermined time intervals to generate sample data.
- the frequency analysis unit 331 calculates frequency spectra at a number of locations (data positions) on the RF data by performing FFT processing on the sample data group.
- the “frequency spectrum” means “frequency distribution of intensity at a certain reception depth z” obtained by subjecting the sample data group to FFT processing.
- “intensity” as used herein refers to parameters such as the voltage of the echo signal, the power of the echo signal, the sound pressure of the ultrasonic echo, the acoustic energy of the ultrasonic echo, the amplitude and time integral value of these parameters, and combinations thereof. Points to either.
- the voltage of the echo signal is employed as the intensity
- the frequency analysis unit 331 generates frequency spectrum data (hereinafter also referred to as spectrum data) based on the frequency component V (f, L) of the voltage amplitude. It is assumed that it is generated.
- f is the frequency.
- the frequency analysis unit 331 divides the frequency component V (f, L) of the voltage amplitude by the reference voltage V c , takes a common logarithm (log), and performs logarithmic conversion processing expressed in decibels,
- the spectral data F (f, L) given by the following equation (1) is generated by multiplying by the constant A.
- F (f, L) A ⁇ log ⁇ V (f, L) / V c ⁇ (1)
- log is a common logarithm (hereinafter the same).
- the frequency spectrum of the echo signal tends to vary depending on the properties of the living tissue scanned with ultrasonic waves. This is because the frequency spectrum has a correlation with the size, number density, acoustic impedance, and the like of the scatterer that scatters ultrasonic waves.
- the “characteristics of the biological tissue” referred to here includes, for example, malignant tumor (cancer), benign tumor, endocrine tumor, mucinous tumor, normal tissue, cyst, vascular vessel and the like.
- FIG. 4 is a diagram schematically showing a data array in one sound ray SR k of the ultrasonic signal.
- a white or black rectangle in the sound ray SR k means data at one sample point.
- the data located on the right side is sample data from a deeper location when measured from the ultrasonic transducer 21 along the sound ray SR k (see the arrow in FIG. 4).
- the sound ray SR k is sample data obtained by sampling the RF data sampled from the echo signal by the A / D conversion process in the transmission / reception unit 31 and further sampling the frequency analysis unit 331 as described above.
- FIG. 4 is a diagram schematically showing a data array in one sound ray SR k of the ultrasonic signal.
- a white or black rectangle in the sound ray SR k means data at one sample point.
- the data located on the right side is sample data from a deeper location when measured from the ultrasonic transducer 21 along the sound ray SR k (see the arrow in FIG
- a sample data group needs to have a power number of 2 data.
- a process for generating a normal sample data group is performed by inserting zero data in an insufficient amount. This point will be described in detail when the processing of the frequency analysis unit 331 is described (see FIG. 9).
- the frequency analysis unit 331 calculates the frequency component V (f, L) of the voltage amplitude by executing the FFT process, and the spectrum data F (f, L) based on the above equation (1). ) And output to the single regression analysis unit 332.
- FIG. 5 is a diagram illustrating an example of spectrum data calculated by the frequency analysis unit 331.
- the horizontal axis is the frequency f.
- the vertical axis represents the spectrum data F (f, L) given by the above equation (1). It will be described later linear L 10 shown in FIG.
- the curve and the straight line are composed of a set of discrete points.
- the lower limit frequency f L and the upper limit frequency f H of the frequency band used for the subsequent calculation are the frequency band of the ultrasonic transducer 21 and the frequency band of the pulse signal transmitted by the transmitting / receiving unit 31. It is a parameter determined based on the above.
- the frequency band determined by the lower limit frequency f L and the upper limit frequency f H is referred to as “frequency band U”.
- the single regression analysis unit 332 includes an approximation unit 332a that calculates a feature amount of spectrum data (hereinafter referred to as a feature amount before correction) by approximating the plurality of spectrum data output from the frequency analysis unit 331 with a straight line, and an approximation unit An attenuation correction unit 332b that calculates a feature amount by correcting the frequency-dependent attenuation with respect to the pre-correction feature amount calculated by 332a.
- a feature amount of spectrum data hereinafter referred to as a feature amount before correction
- the approximating unit 332a performs a single regression analysis of spectrum data in a predetermined frequency band and approximates the spectrum data with a linear expression (regression line), thereby calculating a pre-correction feature quantity characterizing the approximated primary expression.
- a single regression analysis is a regression analysis when there is only one type of independent variable.
- the independent variable of the single regression analysis in this embodiment corresponds to the frequency f. For example, when the spectrum data is in the state of C 1 shown in FIG. 5, the approximating unit 332a performs a single regression analysis in the frequency band U and obtains a straight line L 10 that is a regression line of the spectrum data C 1 .
- the mid-band fit c 0 a 0 f M + b 0 is calculated as a feature amount before correction.
- the spectral data C 1 is approximated to a linear expression by expressing the spectral data C 1 with the parameters of the linear expression (slope a 0 , intercept b 0 , midband fit c 0 ) that characterizes the straight line L 10. Become.
- the slope a 0 and the intercept b 0 have a correlation with the size of the scatterer that scatters ultrasonic waves, the scattering intensity of the scatterer, the number density (concentration) of the scatterer, and the like. It is thought that there is.
- the midband fit c 0 gives the intensity of the spectrum at the center within the effective frequency band. Therefore, the midband fit c 0 is considered to have a certain degree of correlation with the brightness of the B-mode image in addition to the size of the scatterer, the scattering intensity of the scatterer, and the number density of the scatterers.
- the approximating unit 332a outputs the pre-correction feature values a 0 , b 0 , and c 0 to the attenuation correcting unit 332b.
- the approximation unit 332a may approximate the spectrum data with a second-order or higher-order polynomial by regression analysis.
- the attenuation correction unit 332b The correction performed by the attenuation correction unit 332b will be described.
- the amplitude of ultrasonic waves attenuates exponentially. Therefore, when the amplitude is logarithmically converted and expressed in decibels, the attenuation amount A (f, z) generated while the ultrasonic wave reciprocates between the reception depth 0 and the reception depth z is a linear change before and after the reciprocation. It can be expressed as (difference in decibel expression). It is known that the attenuation amount A (f, z) of the amplitude depends on the frequency when the observation target is a living body, and is greatly attenuated at a high frequency and small at a low frequency.
- the value of the attenuation rate ⁇ is stored in advance in the storage unit 37, and the attenuation correction unit 332b appropriately reads the value of the attenuation rate ⁇ from the storage unit 37 and uses it.
- the attenuation correction unit 332b displays the region name.
- An appropriate value of the attenuation rate ⁇ corresponding to the tissue name is read out and used for the following attenuation correction.
- the attenuation correction unit 332b uses the value for the following attenuation correction.
- the attenuation correction unit 332b uses 0.55 dB / cm / MHz for the following attenuation correction.
- the attenuation correction unit 332b performs attenuation correction according to the following equations (3) to (5) on the pre-correction feature values (slope a 0 , intercept b 0 , midband fit c 0 ) extracted by the approximation unit 332a. As a result, corrected feature quantities a, b, and c (hereinafter simply referred to as feature quantities) are calculated.
- the attenuation correction unit 332b performs correction with a larger correction amount as the ultrasonic reception depth z is larger.
- the correction relating to the intercept is an identity transformation. This is because the intercept is a frequency component corresponding to a frequency of 0 (Hz) and is not affected by attenuation.
- FIG. 6 is a diagram illustrating a straight line having the feature amounts a, b, and c calculated by the attenuation correction unit 332b as parameters.
- the estimation unit 333 calculates the feature amount a and the feature amount c for which the single regression analysis unit 333 performs attenuation correction, and constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ stored in the storage unit 37. Used to estimate the number density n and diameter d, the common logarithms logn and logd that are actually in their order.
- the feature quantity a (slope) and feature quantity c (midband fit) are orders (number of digits ⁇ 1) that are approximate values of the number density n of the scatterers and the diameter d of the scatterers, that is, , Logn and logd are assumed to have a linear relationship, and the estimation unit 333 estimates logn and logd based on the following equation (10) derived from equations (7) and (8) of the regression plane: .
- the estimation unit 333 outputs the estimated logn and / or logd to the image processing unit 34 as a physical quantity.
- a control object is prepared.
- a plurality of artificially created reference phantoms will be described as an example of a control object.
- the reference phantom is formed by mixing a large number of particles as a scatterer in a uniform medium and solidifying.
- the scatterers are preliminarily made of the same material so that the mass density, sound speed, and acoustic impedance are the same among the scatterers. Sifted and screened to equal diameters.
- the medium is uniformly mixed so that there is no bias, and the number density is uniform in the reference phantom.
- the material, mass density, sound velocity, acoustic impedance, diameter, and number density of the scatterer in the reference phantom are known values and are uniform in the reference phantom.
- the material, mass density, sound velocity, and acoustic impedance of the medium are also known values and are uniform within the reference phantom.
- the attenuation rate [dB / cm / MHz] is also uniform. Then, by changing these parameters, a plurality of reference phantoms are created.
- the characteristic amount c i is excluded from the influence of attenuation by using the depth at which the spectrum data of the i-th reference phantom is calculated and Expression (5) based on the attenuation rate ⁇ i of the i-th reference phantom. , Depth independent.
- N data sets (c 1 , n 1 , d 1 ), (c 2 , n 2 , d 2 ), (c 3 , n) consisting of the number density of these scatterers, the diameter of the scatterers, and the feature quantities. 3 , d 3 ),... (C N , n N , d N ).
- FIG. 7 shows an orthogonal coordinate system in which a midband fit (characteristic amount c), a common logarithm (logn) of the number density of the scatterer, and a common logarithm (logd) of the diameter of the scatterer are taken on axes orthogonal to each other. Is shown.
- a plot P 1 (logn 1 , logd 1 , c 1 ) corresponding to the first reference phantom and a plot P 2 (logn 2 , logd 2 , c) corresponding to the second reference phantom are previously stored.
- Plot P 1, P 2, P 3 for the feature quantity c, ⁇ ⁇ ⁇ , and regression plane PL of the P N is the plot P 1, P 2, P 3, ⁇ ⁇ ⁇ , the difference between P N (error), that is, the line segment P 1 P 1 ⁇ , P 2 P 2 ⁇ , P 3 P 3 ⁇ , ⁇ , is a plane square sum of P N P N ⁇ distance is minimized.
- P i ⁇ is an intersection of a straight line passing through the plot P i and parallel to the axis of interest (here, the coordinate axis of the feature quantity c) and this plane.
- the multiple regression analysis is a regression analysis when there are two or more independent variables.
- the independent variables of the multiple regression analysis in the present embodiment correspond to the diameter d of the scatterer and the number density n of the scatterer.
- planar equations can be written as linear equations. Since the regression plane PL for the feature quantity c shown in FIG. 7 is in a three-dimensional space, it can be written as an equation (formula (7)) expressing the feature quantity c as a linear combination of two variables (logn, logd). it can.
- ⁇ , ⁇ , and ⁇ are real constants that determine the plane.
- Finding the regression plane PL for the feature quantity c is equivalent to finding the values of ⁇ , ⁇ , and ⁇ .
- the regression plane PL can be considered in the same manner as the feature quantity c, and the feature quantity a is written as an equation (formula (8)) expressed by a linear combination of two variables (logn, logd). Can do.
- ⁇ ′, ⁇ ′, and ⁇ ′ are real constants that determine the plane.
- Obtaining the regression plane PL for the feature quantity a is equivalent to obtaining the values of ⁇ ′, ⁇ ′, and ⁇ ′. From the above equations (7) and (8), the following equation (9) is obtained.
- the following formula (10) is obtained from the formula (9).
- the regression plane PL passes through points (coordinates of P 1 , P 2 ,..., P N ) whose coordinates are the average of the number density n i , diameter d i , and feature quantity c i of the scatterers. Therefore, the following equation (14) is obtained from the equation (7).
- the constant ⁇ can be obtained by substituting ⁇ and ⁇ obtained by the above equation (13) into the following equation (14).
- Constants ⁇ ′, ⁇ ′, and ⁇ ′ can be obtained using (a 3 , n 3 , d 3 ),..., (A N , n N , d N ).
- the constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, and ⁇ ′ have been obtained, and thus the preparation for the estimation unit 333 to estimate unknown logn and logd from the observation target can be explained.
- the feature quantity c and feature quantity a of the observation target obtained through the ultrasonic endoscope 2 logd which is the number of digits ⁇ 1 of the diameter d of the scatterer in the observation target, and the number of scatterers Logn, which is the number of digits of density n-1, is also considered to follow the physical trend obtained from the reference phantom. Therefore, when the data set (n, d, c) from the observation target is plotted in FIG. 7, it should be estimated somewhere on the regression plane PL.
- this data set (n, d, c) satisfies the equation (7) of the regression plane PL.
- the data set (n, d, a) from the observation target also satisfies Expression (8). Since n, d, c, and a to be observed satisfy Expression (7) and Expression (8), Expression (10) is satisfied. Therefore, the estimation unit 333 substitutes the feature quantity c and the feature quantity a from the observation target in this way into the equation (10), and estimates logn and logd.
- the acquired constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ are stored in the relation information storage unit 371 built in the storage unit 37 via the input unit 35 before shipment from the factory.
- An important point in the present embodiment is that the estimation unit 333 estimates logn and logd based on a multiple regression analysis method using a feature quantity based on an echo signal from a control object whose physical quantity is known. It is.
- the image processing unit 34 includes a B-mode image data generation unit 341 that generates B-mode image data that expresses the amplitude of the echo signal in luminance, and the B-mode image data generated by the B-mode image data generation unit 341.
- a physical quantity image data generation unit 342 (physical quantity information generation unit) that generates physical quantity image data to be displayed together with the B-mode image by associating the physical quantity (logn and / or logd) estimated by the estimation unit 333 with visual information. .
- the B-mode image data generation unit 341 performs signal processing using known techniques such as gain processing and contrast processing on the B-mode reception data received from the signal processing unit 32, and displays an image on the display device 4.
- B-mode image data is generated by thinning out data according to the data step width determined according to the range.
- the B-mode image is a grayscale image in which values of R (red), G (green), and B (blue), which are variables when the RGB color system is adopted as a color space, are matched.
- the B-mode image data generation unit 341 performs coordinate conversion for rearranging the B-mode reception data from the signal processing unit 32 so that the scanning range can be spatially represented correctly, and then performs interpolation processing between the B-mode reception data. As a result, the gaps between the B-mode reception data are filled, and B-mode image data is generated.
- the B-mode image data generation unit 341 outputs the generated B-mode image data to the physical quantity image data generation unit 342.
- the physical quantity image data generation unit 342 generates physical quantity image data by superimposing visual information related to the physical quantity estimated by the estimation unit 333 on each pixel of the image in the B-mode image data.
- Physical quantity image data generating unit 342, for example, FIG. 4 one shown in the sample data group F j (j 1,2, ⁇ , K) with respect to a pixel area corresponding to the data amount of the sample data group F j
- Visual information related to the physical quantity corresponding to the characteristic quantity of the frequency spectrum calculated from the above is assigned.
- the physical quantity image data generation unit 342 generates physical quantity image data by associating one of logn and logd with a hue as visual information.
- the physical quantity image data generation unit 342 may generate physical quantity image data by associating a hue with one of logn and / or logd and associating brightness with the other.
- Examples of visual information related to the physical quantity include variables in a color space constituting a predetermined color system such as hue, saturation, brightness, luminance value, R (red), G (green), and B (blue). be able to.
- the physical quantity image data generated by the physical quantity image data generation unit 342 corresponds to a region of interest (ROI) divided by a specific depth width and sound ray width in the scanning region S shown in FIG. Physical quantity image data such that the physical quantity image of the area is displayed on the display device 4 is generated.
- ROI region of interest
- the control unit 36 is realized using a general-purpose processor such as a CPU having calculation and control functions, or a dedicated integrated circuit such as an ASIC or FPGA.
- the control unit 36 reads out information stored and stored in the storage unit 37 from the storage unit 37 and executes various arithmetic processes related to the operation method of the ultrasonic diagnostic apparatus 3 to control the ultrasonic diagnostic apparatus 3 in an integrated manner. To do.
- the control unit 36 may be configured using a general-purpose processor or a dedicated integrated circuit shared with the signal processing unit 32 and the calculation unit 33.
- the storage unit 37 stores a plurality of feature amounts calculated for each frequency spectrum by the attenuation correction unit 332b and image data generated by the image processing unit 34.
- the storage unit 37 includes a relational information storage unit 371 that stores relational expressions (constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′) when the estimation unit 333 performs estimation processing.
- the storage unit 37 has information necessary for amplification processing (relationship between the amplification factor and the reception depth shown in FIG. 2), information necessary for logarithmic conversion processing (see Equation (1), for example, A, V c )), information on window functions (Hamming, Hanning, Blackman, etc.) necessary for frequency analysis processing, and the like are stored.
- the storage unit 37 stores various programs including an operation program for executing the operation method of the ultrasonic diagnostic apparatus 3.
- the operation program can be recorded on a computer-readable recording medium such as a hard disk, a flash memory, a CD-ROM, a DVD-ROM, or a flexible disk and widely distributed.
- the various programs described above can also be obtained by downloading via a communication network.
- the communication network here is realized by, for example, an existing public line network, LAN (Local Area Network), WAN (Wide Area Network), etc., and may be wired or wireless.
- the storage unit 37 having the above configuration is realized by using a ROM (Read Only Memory) in which various programs are installed in advance, a RAM (Random Access Memory) storing a calculation parameter and data of each process, a hard disk, and the like. Is done.
- ROM Read Only Memory
- RAM Random Access Memory
- FIG. 8 is a flowchart showing an outline of processing performed by the ultrasonic diagnostic apparatus 3 having the above configuration.
- the ultrasound diagnostic apparatus 3 receives an echo signal as a measurement result of an observation target by the ultrasound transducer 21 from the ultrasound endoscope 2 (step S1).
- the signal amplifying unit 311 that has received the echo signal from the ultrasonic transducer 21 amplifies the echo signal (step S2).
- the signal amplifying unit 311 performs amplification (STC correction) of the echo signal based on the relationship between the amplification factor and the reception depth shown in FIG. 2, for example.
- the transmitter / receiver 31 samples and discretizes both the echo signal amplified at an appropriate sampling frequency (for example, 50 MHz) and the original echo signal that is not amplified, and generates RF data A and RF data N from each of them. Then, the former is output to the B-mode image data generation unit 341 and the latter is output to the frequency analysis unit 331.
- the B-mode image data generation unit 341 generates B-mode image data using the RF data A output from the transmission / reception unit 31, and outputs the B-mode image data to the physical quantity image data generation unit 342 (step S3).
- the physical quantity image data generation unit 342 does not process the B-mode image data and outputs it to the display device 4 as it is.
- the display device 4 that has received the B-mode image data displays a B-mode image corresponding to the B-mode image data (step S4).
- control unit 36 confirms whether “display” or “non-display” of the physical quantity image is selected by a user such as an operator via a button or menu (not shown) of the input unit 35 (step S5). ).
- the control unit 36 outputs a physical quantity image creation start command to each unit constituting the calculation unit 33 (step S5: Yes). If it is confirmed that “Hide” is selected, a physical quantity image creation start command is not issued (step S5: No).
- the unit 33 performs processing after step S6 described later.
- the transmission / reception unit 31, the signal amplification unit 311, the signal processing unit 32, the B-mode image data generation unit 341, and the physical quantity image data generation unit 342 of the ultrasonic diagnostic apparatus 3 perform the above steps regardless of whether there is a physical quantity image creation start command.
- the processes from S1 to S4 are repeated. Therefore, while the user instructs the input unit 35 to “non-display” the physical quantity image, the B-mode image is repeatedly displayed on the display device 4 every time the ultrasonic transducer 21 scans within the observation target.
- FIG. 9 is a flowchart showing an outline of the processing executed by the frequency analysis unit 331 in step S6.
- the frequency analysis process will be described in detail with reference to the flowchart shown in FIG.
- the frequency analysis unit 331 sets k 0 as a counter k for identifying a sound ray to be analyzed (step S21).
- This initial value k 0 is the number of the rightmost sound ray in the analysis range in FIG.
- the frequency analysis unit 331 sets an initial value Z (k) 0 of a data position (corresponding to a reception depth) Z (k) that represents a series of data groups (sample data group) acquired for FFT processing.
- FIG. 4 shows a case where the eighth data position of the sound ray SR k is set as the initial value Z (k) 0 as described above.
- This initial value Z (k) 0 is the shallowest reception depth in the analysis range on the sound ray SR k .
- the frequency analysis unit 331 acquires a sample data group (step S23), and causes the window function stored in the storage unit 37 to act on the acquired sample data group (step S24).
- the window function By applying the window function to the sample data group in this way, it is possible to avoid the sample data group from becoming discontinuous at the boundary and to prevent the occurrence of artifacts.
- the frequency analysis unit 331 determines whether or not the sample data group at the data position Z (k) is a normal data group (step S25).
- the sample data group needs to have the number of powers of two.
- the number of data in the normal sample data group is 2 n (n is a positive integer).
- the sample data groups F 1 , F 2 , F 3 ,..., F K-1 are all normal.
- step S25 If the result of determination in step S25 is that the sample data group at data position Z (k) is normal (step S25: Yes), the frequency analysis unit 331 proceeds to step S27 described later.
- step S25 if the sample data group at the data position Z (k) is not normal (step S25: No), the frequency analysis unit 331 inserts zero data for the shortage to obtain a normal sample data group. Generate (step S26). A window function is applied to the sample data group determined to be not normal in step S25 (for example, the sample data group F K in FIG. 4) before adding zero data. For this reason, even if zero data is inserted into the sample data group, data discontinuity does not occur. After step S26, the frequency analysis unit 331 proceeds to step S27 described later.
- step S27 the frequency analysis unit 331 calculates V (f, L) that is the frequency component of the amplitude by performing an FFT operation using the sample data group. Thereafter, the frequency analysis unit 331 performs logarithmic conversion processing on V (f, L) to obtain spectrum data F (f, L) (step S27).
- the frequency analysis unit 331 changes the data position Z (k) by the step width D (step S28).
- the step width D it is assumed that the storage unit 37 stores in advance the operator's input value via the input unit 35.
- the step width D is as small as possible.
- the amount of calculation in the frequency analysis unit 331 is desired to be reduced.
- a value larger than the data step width may be set as the step width D.
- the frequency analysis unit 331 determines whether or not the data position Z (k) is larger than the maximum value Z (k) max in the sound ray SR k (step S29).
- This maximum value Z (k) max is the deepest reception depth of the analysis range on the sound ray SR k .
- the frequency analysis unit 331 increases the counter k by 1 (step S30). This means that the processing is shifted to the next sound ray.
- the frequency analysis unit 331 returns to step S23.
- the frequency analysis unit 331 determines whether or not the counter k is greater than the maximum value k max (step S31). When the counter k is larger than k max (step S31: Yes), the frequency analysis unit 331 ends a series of frequency analysis processing. On the other hand, when the counter k is equal to or less than k max (step S31: No), the frequency analysis unit 331 returns to step S22.
- This maximum value k max is the number of the leftmost sound ray in the analysis range in FIG.
- the frequency analysis unit 331 performs the FFT operation a plurality of times for each depth for each of (k max ⁇ k 0 +1) sound rays in the analysis target region.
- the result of the FFT operation is stored in the storage unit 37 together with the reception depth and the reception direction.
- the frequency analysis unit 331 reads these values as appropriate and performs the processing of FIG. When the default value is read, the frequency analysis unit 331 performs frequency analysis processing on the entire scanning range.
- these four types of values k 0 , k max , Z (k) 0 , and Z (k) max can be changed by inputting a region of interest instruction by a user such as an operator through the input unit 35. If it has been changed, the frequency analysis unit 331 performs the frequency analysis process only in the region of interest for which an instruction has been input.
- the single regression analysis unit 332 calculates pre-correction feature values of the plurality of spectrum data acquired by the frequency analysis unit 331, and sets the pre-correction feature values of each spectrum data.
- attenuation correction for eliminating the influence of ultrasonic attenuation is performed to calculate the feature amount of each spectrum data (steps S7 to S8).
- step S ⁇ b> 7 the approximating unit 332 a calculates a pre-correction feature amount corresponding to each spectral data by performing a single regression analysis on each of a plurality of spectral data corresponding to positions within the analysis range generated by the frequency analyzing unit 331.
- Step S7 the approximating unit 332a approximates each spectrum data with a linear expression by performing a single regression analysis, and calculates a slope a 0 , an intercept b 0 , and a midband fit c 0 as pre-correction feature values.
- the straight line L 10 shown in FIG. 5 the approximation unit 332a is the regression line approximated by simple linear regression analysis to spectral data C 1 of the frequency band U.
- the attenuation correction unit 332b performs attenuation correction using the attenuation rate ⁇ on the pre-correction feature amount obtained by the approximation unit 332a approximating each spectrum data, so that the feature amount after attenuation correction is performed. Is calculated and stored in the storage unit 37 (step S8).
- a straight line L 1 illustrated in FIG. 6 is an example of a straight line obtained by the attenuation correction unit 332b performing the attenuation correction process.
- f sp is the data sampling frequency
- v s is the sound velocity
- D is the data step width
- n S is the number of data steps from the first data of the sound ray up to the data position of the sample data group to be processed
- Z 0 is the shallowest reception depth in the analysis range.
- the data sampling frequency f sp is 50 MHz
- the sound velocity vs is 1530 m / sec
- the estimation unit 333 includes the feature amount a and the feature amount c that have been subjected to attenuation correction by the single regression analysis unit 332 and constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, stored in the relationship information storage unit 371.
- Logn and / or logd that is a logarithm of number density n and diameter d are estimated using ⁇ ′ (step S9: estimation step).
- the estimation unit 333 outputs the estimated logn and / or logd to the physical quantity image data generation unit 342 as a physical quantity.
- the physical quantity image data generation unit 342 superimposes visual information (for example, hue) associated with the physical quantity estimated in step S9 on each pixel in the B mode image data generated by the B mode image data generation unit 341. Image data is generated (step S10: physical quantity information generation step).
- FIG. 10 is a diagram schematically illustrating a display example of the feature amount image on the display device 4.
- a feature amount image 201 shown in the figure includes a superimposed image display unit 202 that displays an image in which visual information related to a physical amount is superimposed on a B-mode image, and an information display unit 203 that displays identification information of an observation target.
- the information display unit 203 may further display physical quantity or feature quantity information, approximate expression information, gain and contrast information, and the like.
- a B-mode image corresponding to the physical quantity image may be displayed side by side with the physical quantity image.
- steps S1 to S11 the processes of steps S2 to S4 and the processes of steps S5 to S10 may be performed in parallel.
- the scatterer diameter and the number density of the scatterers were explained as physical quantities to be observed, and logarithmic transformation was taken as an example of variable transformation. However, this is not limited to this combination, and may be another physical quantity or another variable conversion. If the desired physical quantity can be converted into a variable whose feature value changes linearly or slowly, the converted variable can be reduced to a linear multiple regression analysis or estimated by approximation, The desired physical quantity can be estimated to some extent. In the first embodiment, it was possible to estimate the order of the diameter of the scatterer to be observed and the number density of the scatterers (digit number ⁇ 1).
- the characteristic amount calculated by the single regression analysis unit 332 and the relational expressions calculated using the reference phantom (constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′). , ⁇ ′), and the estimation unit 333 estimates logn and / or logd obtained by taking the logarithm of the number density n and the diameter d, so that the number density and / or size (diameter) of the scatterer is estimated. It was possible to estimate directly. Accordingly, it is possible to easily and reliably carry out pathological interpretation of what kind of pathology corresponds to the value calculated as the feature amount without requiring skill.
- the constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ are obtained on the basis of the attenuation-corrected feature values from the reference phantom.
- the above estimation can be made more accurately regardless of the difference in the attenuation rate between the reference phantom and the reference phantom.
- spectrum data can be calculated only for a region of interest that is delimited by a specific depth width and sound ray width input by an instruction. Therefore, it is possible to reduce the calculation amount related to the calculation and increase the frame rate.
- the region of interest is divided into a sector shape by the depth width and the sound ray width, but is not limited to this example, and may be a rectangle or an ellipse, or may be another shape.
- the single regression analysis unit 332 may set optimal attenuation rates individually for the set region of interest and for the outside of the region of interest.
- FIG. 11 is a block diagram showing a configuration of an ultrasonic diagnostic system 1a including an ultrasonic diagnostic apparatus according to a modification of the first embodiment of the present invention.
- the calculation unit 33 of the ultrasonic diagnostic apparatus 3 further includes a variable conversion unit 334 with respect to the configuration of the ultrasonic diagnostic system 1 according to Embodiment 1 described above.
- the variable conversion unit 334 converts logn and / or logd estimated by the estimation unit 333 into n and / or d. Specifically, the estimated value of logn and / or logd is substituted into an index of 10 to be n and / or d.
- the variable conversion unit 334 outputs the converted number density n and / or diameter d to the physical quantity image data generation unit 342.
- the physical quantity image data generation unit 342 superimposes the visual information related to the physical quantity (number density n and / or diameter d) converted by the variable conversion unit 334 on each pixel of the image in the B-mode image data, thereby generating a physical quantity image. Generate data.
- Physical quantity image data generating unit 342, for example, FIG. 4 one shown in the sample data group F j (j 1,2, ⁇ , K) with respect to a pixel area corresponding to the data amount of the sample data group F j
- Visual information related to the physical quantity corresponding to the characteristic quantity of the frequency spectrum calculated from the above is assigned.
- the display device 4 displays a physical quantity image corresponding to the physical quantity image data generated by the physical quantity image data generation unit 342 under the control of the control unit 36.
- FIG. 12 is a diagram schematically illustrating a display example of the feature amount image on the display device 4.
- a feature amount image 201 shown in the figure includes a superimposed image display unit 202 that displays an image on which visual information related to a physical amount is superimposed on a B-mode image, and an information display unit 203 that displays identification information of an observation target.
- the information display unit 203 displays the number density n and / or the diameter d of the scatterers converted by the variable conversion unit 334 as physical quantity information.
- the logn and / or logd estimated by the estimation unit 333 are subjected to variable conversion so that the number density n and the diameter d of the scatterer are displayed as physical quantities. It was possible to estimate using visual information directly related to size (diameter). Accordingly, it is possible to easily and reliably carry out pathological interpretation of what kind of pathology corresponds to the value calculated as the feature amount without requiring skill.
- the feature quantity c, Logn and loga having a substantially linear relationship with the feature amount a can be used.
- the number density n of the scatterer and the diameter d of the scatterer which are the physical quantities originally desired by changing the variables of logn and loga, not only the order (digits ⁇ 1) but also the value itself is linearly overlapped. It can be estimated by regression analysis.
- the second embodiment has the same configuration as that of the ultrasonic diagnostic system including the ultrasonic diagnostic apparatus according to the first embodiment described above.
- FIG. 1 is common.
- the single regression analysis unit 332 has been described as calculating the feature quantities a, b, and c by single regression analysis.
- the single regression analysis unit 332 uses the feature quantity to be observed.
- the attenuation rate ⁇ is calculated.
- the attenuation rate ⁇ can be calculated using, for example, the spectrum data F (f, L) described above.
- the characteristic amount a which is the slope of the regression line with respect to the frequency f of the spectrum data F (f, L) is obtained by regression analysis, then the further slope of the slope with respect to the round trip distance L is obtained, and further ⁇ 1 is obtained. It is calculated by multiplying.
- the estimation unit 333 has been described as estimating logn and / or logd obtained by taking the logarithm of the number density n and the diameter d.
- the estimation unit 333 includes In addition to logn and / or logd, which is logarithm of number density n and diameter d, scattering intensity (hereinafter, scattering intensity is assumed to be r) is estimated.
- the scattering intensity here is the amplitude reflectance, energy reflectance, and / or function of the scatterer and the medium.
- the scattering intensity is an amplitude reflectance or energy reflectance defined as follows.
- Energy reflectance
- the estimation unit 333 includes the feature amount a and the feature amount c that have been subjected to attenuation correction by the single regression analysis unit 332, the attenuation rate ⁇ as the feature amount, and the constant ⁇ stored in the storage unit 37. , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′, ⁇ ′, ⁇ ′′, ⁇ ′′, ⁇ ′′, ⁇ ′′, and the logarithm of the number density n and the diameter d was taken. Estimate logn and logd and the scattering intensity r.
- the estimation unit 333 Based on the following equation (19) derived from equations (15) to (17) of the regression plane (that is, a three-dimensional solid) in the dimensional space, logn, logd, and scattering intensity r are estimated.
- the estimation unit 333 outputs the estimated logn, logd and / or scattering intensity r to the image processing unit 34 as a physical quantity.
- the constants ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′, ⁇ ′, ⁇ ′′, ⁇ ′′, ⁇ ′′, ⁇ ′′ will be described.
- the constants ⁇ , ⁇ , ⁇ , and ⁇ are formed by uniformly mixing, distributing, and solidifying a material with adjusted scatterer size (diameter), number density, and scattering intensity, and the scatterer size (diameter).
- the ultrasonic wave is transmitted to a reference phantom that is known in advance, and is calculated based on the obtained ultrasonic echo.
- the feature amount c (midband fit) can be calculated and obtained.
- the feature quantity c is calculated using N reference phantoms having different combinations of the diameter, number density, and scattering intensity of the scatterers.
- the number density of the scatterers of the i-th reference phantom is n i
- the diameter is d i
- the scattering intensity is r i
- the attenuation rate is ⁇ i.
- c i be the characteristic amount (mid-band fit) obtained by the phantom (1 ⁇ i ⁇ N).
- the characteristic amount c i is excluded from the influence of attenuation by using the depth at which the spectrum data of the i-th reference phantom is calculated and Expression (5) based on the attenuation rate ⁇ i of the i-th reference phantom. , Depth independent.
- the average of the number density n i , diameter d i , scattering intensity r i and feature value c i of the scatterers over all reference phantoms is obtained.
- a matrix G and a column vector Y shown in the following expressions (20) and (21) are defined.
- the constants ⁇ , ⁇ , and ⁇ of the equation of the regression plane in the four-dimensional plane can be obtained by the following equation (22) defined by equations (20) and (21).
- t on the left shoulder indicates a transposed matrix
- -1 on the right shoulder indicates an inverse matrix.
- Equation (23) is obtained.
- the constants ⁇ , ⁇ , and ⁇ obtained by the above equation (22) can be substituted into the following equation (23) to obtain the constant ⁇ .
- the constants ⁇ , ⁇ , ⁇ , and ⁇ in the above equation (15) can be obtained using N reference phantoms.
- the feature quantity a i is calculated using N reference phantoms, and the constants ⁇ ′, ⁇ ′, and ⁇ ′ are calculated.
- ⁇ ′ can be obtained.
- the constants ⁇ ′′, ⁇ ′′, ⁇ ′′, and ⁇ ′′ in the above equation (17) are similarly measured using the N reference phantoms, and the attenuation rate ⁇ i measured again or a known attenuation rate.
- Constants ⁇ ′′, ⁇ ′′, ⁇ ′′, and ⁇ ′′ can be obtained using ⁇ i .
- the acquired constants ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′, ⁇ ′, ⁇ ′′, ⁇ ′′, ⁇ ′′, ⁇ ′′ are stored in the storage unit 37.
- the feature quantity c, the feature quantity a, the attenuation rate ⁇ , and the logd which is the number of digits ⁇ 1 of the diameter d of the scatterer in the observation object, obtained through the ultrasonic endoscope 2, It is considered that logn, which is the number -1 of the number density n of the scatterers, and the scattering intensity r of the scatterers also follow the physical tendency obtained from the reference phantom. Therefore, the data set (n, d, r, c) satisfies the regression plane equation (15).
- a data set (n, d, r, a) from the observation target satisfies Expression (16)
- a data set (n, d, r, ⁇ ) from the observation target satisfies Expression (17).
- n, d, r, c, a, and ⁇ to be observed satisfy Expression (15), Expression (16), and Expression (17), Expression (19) is satisfied. Therefore, the estimation unit 333 substitutes the feature quantity c from the observation target, the feature quantity a, and the attenuation rate ⁇ of the observation target as the feature quantity into the equation (19), and estimates logn, logd, and the scattering intensity r. To do.
- the relational expressions (constants ⁇ , ⁇ , ⁇ , ⁇ ) calculated using the feature quantity calculated by the single regression analysis unit 332, the attenuation rate, and the reference phantom. , ⁇ ′, ⁇ ′, ⁇ ′, ⁇ ′, ⁇ ′′, ⁇ ′′, ⁇ ′′), and logn in which the estimation unit 333 takes the logarithm of the number density n and the diameter d.
- Logd and / or scattering intensity r are estimated so that the number density, size (diameter) and / or scattering intensity of the scatterer can be directly estimated. Accordingly, it is possible to easily and reliably carry out pathological interpretation of what kind of pathology corresponds to the value calculated as the feature amount without requiring skill.
- the attenuation rate ⁇ is used as the physical quantity.
- the present invention is not limited to this, and the variance of the feature quantities a and c, the average frequency weighted by the spectrum data, and the sound speed are used.
- the sound velocity has a configuration in which an ultrasonic transducer 21 having a plurality of elements arranged in an array is electronically scanned, and the transmission / reception unit 31 has a multi-channel circuit for beam synthesis corresponding to the plurality of elements. This is estimated from the delay time of the received voltage for each element when the focus condition of the echo signal from the ultrasonic transducer 21 is the best.
- the average frequency is given by the following equation (24) (1 ⁇ q ⁇ N f : N f is an integer greater than 1).
- ⁇ q f q ⁇ F ( f q, L) represents the weighted addition of spectral intensity.
- the scattering intensity of the scatterer as the physical quantity to be observed, the scatterer diameter and the number density of the scatterer, and logarithmic conversion as an example of the variable conversion have been described. However, this is not limited to this combination, and may be another physical quantity or another variable conversion. If the desired physical quantity can be converted into a variable whose feature value changes linearly or slowly, the converted variable can be reduced to a linear multiple regression analysis or estimated by approximation, The desired physical quantity can be estimated to some extent. In the second embodiment, it was possible to estimate the order of the diameter of the scatterer to be observed and the number density of the scatterers (digit number ⁇ 1).
- FIG. 13 is a block diagram showing a configuration of an ultrasonic diagnostic system including the ultrasonic diagnostic apparatus according to Embodiment 3 of the present invention.
- the ultrasonic diagnostic system 1b according to the third embodiment is different from the configuration of the ultrasonic diagnostic system 1 according to the first embodiment described above in that the ultrasonic diagnostic apparatus 3 includes a variable conversion unit 38 and a multiple regression analysis unit 39. Is further provided.
- variable conversion unit 38 acquires the number density n i, the diameter d i, and the attenuation rate ⁇ i of the scatterers of N reference phantoms via the input unit 35 or the storage unit 37 (1 ⁇ i ⁇ N). ).
- Variable conversion unit 38 obtains logn i and logd i converts the acquired number density n i and diameter d i to the logarithm.
- the variable conversion unit 38 outputs logn i and logd i and the attenuation rate ⁇ i to the storage unit 37.
- the ultrasonic transducer 21 transmits ultrasonic waves to the i-th reference phantom among the N reference phantoms. Thereafter, the transmission / reception unit 31, the frequency analysis unit 331, and the single regression analysis unit 332 perform the same processing as the processing performed on the echo signal from the observation target in the first embodiment on the echo signal from the i-th reference phantom. In this way, the ultrasound diagnostic system 1b calculates the feature quantity c i and the feature quantity a i based on the ultrasound echo from the i-th reference phantom (1 ⁇ i ⁇ N).
- the attenuation correction unit 332b obtains the attenuation rate ⁇ i of the i-th reference phantom from the storage unit 37, the depth at which the spectrum data of the i-th reference phantom is calculated, Equations (3) and (5) ) And correcting the attenuation to eliminate the influence of the attenuation from the feature quantity c i and the feature quantity a i . Since the attenuation is uniform in the reference phantom, the feature value c i and the feature value a i do not depend on the depth.
- the single regression analysis unit 332 outputs the feature quantity c i and the feature quantity a i of the scatterer of the i-th reference phantom to the storage unit 37.
- the ultrasonic diagnostic system 1b performs these processes for all N reference phantoms.
- the multiple regression analysis unit 39 acquires all of the N reference phantoms logn i , logd i , feature quantity c i , and feature quantity a i from the storage unit 37 (1 ⁇ i ⁇ N). Then, the multiple regression analysis unit 39 obtains averages of all the reference phantoms of the number density n i , diameter d i , feature quantity c i , and feature quantity a i of the scatterers of the N reference phantoms. After that, the multiple regression analysis unit 39 uses the same calculation method as in the first embodiment and uses the above equations (11) to (14) to calculate the constants ⁇ , ⁇ , ⁇ , ⁇ in the above equations (7) and (8).
- the multiple regression analysis unit 39 outputs the obtained constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ or relational expressions to the relationship information storage unit 371.
- the relation information storage unit 371 stores the received constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ or relational expressions. As described above, the processing until the constant ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ or the relational expression is stored in the relational information storage unit 371 is preferably performed before the transmission of the ultrasonic wave to the observation target. Occasionally. Then, the ultrasonic wave is transmitted to the observation target.
- the transmission / reception unit 31 receives an echo signal from the ultrasonic transducer 21. Thereafter, the transmission / reception unit 31, the frequency analysis unit 331, and the single regression analysis unit 332 perform processing similar to that of the first embodiment on the echo signal from the observation target. In this way, the single regression analysis unit 332 calculates the feature quantity c and the feature quantity a of the observation target that have been appropriately corrected for attenuation by the attenuation correction unit 332b based on the ultrasonic echo from the observation target, and outputs the feature quantity c and the feature quantity a to the estimation unit 333. To do.
- the processes of the estimation unit 333, the physical quantity image data generation unit 342, and the like are the same as those in the first embodiment described above.
- the effects of the first embodiment described above can be obtained, and in the ultrasonic diagnostic apparatus 3, the constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ Since 'is obtained, the update can be performed on a device-by-device basis, for example, when an ultrasonic endoscope having a new ultrasonic transducer is added or a reference phantom is added.
- the constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ are obtained in the ultrasonic diagnostic apparatus 3. Therefore, even when characteristics such as transmission / reception sensitivity vary for each ultrasonic vibrator, it becomes easy to calculate constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ for each body of the ultrasonic vibrator.
- the number density n of the scatterer and its logarithm logn, the diameter d of the scatterer and its logarithm logd can be estimated more accurately and easily regardless of variations.
- constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, and ⁇ ′ are obtained based on the attenuation-corrected feature values from the reference phantom. Logn and logd can be estimated more accurately regardless of the difference in attenuation rate from the reference phantom.
- the third embodiment of the present invention even if the number density n i of the scatterers of the reference phantom and the diameter d i of the scatterers are not directly related to the feature quantities c i and a i , Logn i and logd i that have a substantially linear relationship with the feature quantities c i and a i can be used. Then, imaging of information on the number density n of the scatterer to be observed and the diameter d of the scatterer, which are the physical quantities originally desired, can be realized by reducing the linear multiple regression analysis.
- variable conversion unit 38 and the multiple regression analysis unit 39 according to the third embodiment can be applied to the above-described modification of the first embodiment and the second embodiment.
- FIG. 14 is a block diagram showing a configuration of an ultrasonic diagnostic system including the ultrasonic diagnostic apparatus according to Embodiment 4 of the present invention.
- the relationship information storage unit 371 stores the LUT 371a in contrast to the configuration of the ultrasonic diagnostic system 1 according to the first embodiment described above.
- FIG. 15 is a diagram for explaining a lookup table stored in the ultrasonic diagnostic apparatus according to Embodiment 4 of the present invention.
- FIG. 15 shows, as an example, a look-up table for outputting logn which is a logarithm of the number density n of scatterers as a physical quantity by inputting feature quantities a and c.
- the LUT 371a is a constant ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ obtained by the multiple regression analysis described above, and a plurality of samples extracted at predetermined intervals.
- Logn and logd are calculated from the above equation (10) based on the provisional feature amounts a and c, and the vertical axis is the provisional feature amount c and the horizontal axis is the provisional feature amount a. It is generated by substituting the value of logn.
- a lookup table for outputting logn can be generated based on the constants ⁇ , ⁇ , ⁇ , ⁇ ′, ⁇ ′, ⁇ ′ and the temporary feature amounts a and c. it can.
- the LUT 371a may be created by the ultrasound diagnostic apparatus 3, may be generated by an external computing device, or may be acquired via a network. Note that when generating the look-up table, the feature amounts c i , feature amounts a i, and attenuation rates ⁇ i of N reference phantoms are used (1 ⁇ i ⁇ N).
- These feature quantities are the attenuation rate, the depth at which the spectral data of the reference phantom is calculated, and the look-up table after eliminating the influence of attenuation by using the expressions (5) and (3) and making it independent of the depth. Is generated.
- the relationship information storage unit 371 stores, as the LUT 371a, a lookup table for outputting logn and a lookup table for outputting logd.
- the estimation unit 333 receives the feature quantities a and c from the single regression analysis unit 332, the estimation unit 333 rounds, for example, the first decimal place of the feature quantity a and the second decimal place of the feature quantity c. Thereafter, when outputting logn, the estimation unit 333 reads and refers to a lookup table for outputting logn from the relationship information storage unit 371, and estimates logn. Further, when outputting logd, the estimation unit 333 reads and refers to a lookup table for outputting logd from the relationship information storage unit 371, and estimates logd.
- the effects of the first embodiment described above can be obtained, and the processing time required to calculate the physical quantity can be shortened.
- the lookup table when the lookup table is generated, the influence of attenuation is eliminated from the feature amount of the reference phantom, and the lookup table is generated without depending on the depth. There is no need to prepare a lookup table for each depth, the amount of data is small, and processing is simple.
- the LUT 371a according to the fourth embodiment can be stored in the modification of the first embodiment or the second embodiment.
- a circuit having each function may be configured to be connected by a bus, or a part of the function may be configured to be incorporated in a circuit structure having another function.
- the size of the scatterer is described as being a diameter, but it may be a radius or a volume.
- the medium, material, mass density, sound velocity, acoustic impedance, diameter, number density, etc. are already known as the reference object in the medium whose material, mass density, sound velocity, acoustic impedance are known.
- the reference phantom in which a certain scatterer is mixed uniformly has been described as an example.
- the reference phantom can be replaced with this.
- a specific tissue such as an animal liver may be used as long as the physical quantity is known or accurately measured.
- the physical quantity is described by taking the number density n of the scatterer, the diameter d of the scatterer, and the scattering intensity r of the scatterer as examples.
- the feature amount the spectrum inclination a, the spectrum intercept b, the spectrum midband fit c, and the attenuation factor ⁇ have been described as examples. However, some or all of them may be used.
- Other physical quantities and feature quantities may be used. For example, an amount indicating the shape of the scatterer as a physical quantity, for example, a fractal dimension indicating irregularity may be used. Further, for example, the dispersion of the diameter distribution of the scatterer may be used as the physical quantity. Sound speed or mass density may be used as the feature quantity.
- the display device 4 may display a plurality of physical quantities at the same time. These instructions may be sequentially switched according to the instruction input, or may be displayed at different timings (frames).
- the ultrasonic endoscope 2 having an optical system such as a light guide has been described as an ultrasonic probe.
- the present invention is not limited to the ultrasonic endoscope 2, and the imaging optical system and An ultrasonic probe that does not have an image sensor may be used.
- a thin ultrasonic miniature probe without an optical system may be applied as the ultrasonic probe.
- Ultrasonic miniature probes are usually inserted into the biliary tract, bile duct, pancreatic duct, trachea, bronchi, urethra, ureter, and used to observe surrounding organs (pancreas, lung, prostate, bladder, lymph nodes, etc.).
- an ultrasonic probe an external ultrasonic probe that irradiates ultrasonic waves from the body surface to be observed may be applied.
- the extracorporeal ultrasonic probe is usually used in direct contact with the body surface when observing an abdominal organ (liver, gallbladder, bladder), breast (particularly mammary gland), and thyroid gland.
- the ultrasonic vibrator may be a linear vibrator, a radial vibrator, or a convex vibrator.
- the scanning area is rectangular (rectangular, square), and when the ultrasonic transducer is a radial or convex transducer, the scanning area is fan-shaped or annular.
- the ultrasonic endoscope may be one that mechanically scans the ultrasonic transducer, or a plurality of elements are arranged in an array as the ultrasonic transducer, and the elements involved in transmission and reception are switched electronically. Alternatively, electronic scanning may be performed by delaying transmission / reception of each element.
- the ultrasonic diagnostic apparatus As described above, the ultrasonic diagnostic apparatus, the method for operating the ultrasonic diagnostic apparatus, and the operation program for the ultrasonic diagnostic apparatus according to the present invention are useful for easily and accurately distinguishing tissue properties based on feature quantities. .
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Abstract
Description
図1は、本発明の実施の形態1に係る超音波診断装置3を備えた超音波診断システム1の構成を示すブロック図である。同図に示す超音波診断システム1は、観測対象である観測対象へ超音波を送信し、該観測対象で後方散乱された超音波を受信する超音波内視鏡2と、超音波内視鏡2が取得した超音波信号に基づいて超音波画像を生成する超音波診断装置3と、超音波診断装置3が生成した超音波画像を表示する表示装置4と、を備える。超音波診断装置3は、超音波内視鏡2を一つ、または超音波内視鏡2の同種、異種に関わらず複数を同時に接続することができる。本実施の形態では、超音波内視鏡2が、超音波プローブとして作用する。なお、図1では、実線の矢印が画像にかかる電気信号の伝送を示し、破線の矢印が制御にかかる電気信号の伝送を示している。
F(f,L)=A・log{V(f,L)/Vc} ・・・(1)
ここで、logは常用対数である(以下、同じ)。
A(f,z)=2ζzf ・・・(2)
ここで、比例定数ζは減衰率と呼ばれる量である。また、zは超音波の受信深度であり、fは周波数である。減衰率ζの具体的な値は、観測対象が生体である場合、生体の部位や組織に応じて定まる。正常肝では概ね、0.55dB/cm/MHzである。なお、本実施の形態において、減衰率ζの値は記憶部37に予め記憶されており、減衰補正部332bは適宜、記憶部37から減衰率ζの値を読み出して用いる。入力部35が、超音波内視鏡2による超音波の送信の前に、予め、観測対象の部位名や組織名の入力を術者から受けた場合には、減衰補正部332bは、部位名や組織名に対応した減衰率ζの適当な値を読み出し、以下の減衰補正に用いる。さらに、入力部35が、減衰率ζの値を術者から直接受けた場合には、減衰補正部332bは、その値を以下の減衰補正に用いる。入力部35が、一切の入力を術者から受けなかった場合には、減衰補正部332bは、上記0.55dB/cm/MHzを以下の減衰補正に用いる。
a=a0+2ζz ・・・(3)
b=b0 ・・・(4)
c=c0+A(fM,z)=c0+2ζzfM(=afM+b) ・・・(5)
式(3)、(5)からも明らかなように、減衰補正部332bは、超音波の受信深度zが大きいほど、補正量が大きい補正を行う。また、式(4)によれば、切片に関する補正は恒等変換である。これは、切片が周波数0(Hz)に対応する周波数成分であって減衰の影響を受けないためである。
I=af+b=(a0+2ζz)f+b0 ・・・(6)
で表される。この式(6)からも明らかなように、直線L1は、減衰補正前の直線L10と比較して、傾きが大きく(a>a0)、かつ切片が同じ(b=b0)である。この後、単回帰分析部332は、これら減衰補正された特徴量a、b、cを推定部333へ出力する。
続いて、本発明の実施の形態1の変形例について説明する。上述した実施の形態1では、推定部333が数密度nおよび直径dの対数をとったlognおよび/またはlogdを推定し、物理量画像データ生成部342が、lognおよび/またはlogdに対応する視覚情報をBモード画像に重畳するものとして説明したが、本変形例では、演算部33が、推定部333が推定したlognおよび/またはlogdを、さらに、nおよび/またはdに変換する。図11は、本発明の実施の形態1の変形例に係る超音波診断装置を備えた超音波診断システム1aの構成を示すブロック図である。
続いて、本発明の実施の形態2について説明する。本実施の形態2は、上述した実施の形態1に係る超音波診断装置を備えた超音波診断システムの構成と同様の構成を備える。図1は共通である。上述した実施の形態1では、単回帰分析部332が単回帰分析により特徴量a、b、cを算出するものとして説明したが、本実施の形態では単回帰分析部332が観測対象の特徴量として、これら3特徴量に加えて減衰率ζを算出する。減衰率ζは、例えば上述したスペクトルデータF(f,L)を用いて算出することができる。具体的には、回帰分析によりスペクトルデータF(f,L)の周波数fに対する回帰直線の傾きである特徴量aを求め、次にその傾きの往復距離Lに対するさらなる傾きを求め、さらに-1を乗ずることで求められる。また、上述した実施の形態1では、推定部333が数密度nおよび直径dの対数をとったlognおよび/またはlogdを推定するものとして説明したが、本実施の形態2では、推定部333が、数密度nおよび直径dの対数をとったlognおよび/またはlogdに加えて、散乱強度(以下、散乱強度をrとする)を推定する。ここでいう散乱強度とは、散乱体と媒体の振幅反射率、エネルギー反射率、および/または、それらの関数である。ここで、散乱強度は、以下のように定義される振幅反射率またはエネルギー反射率である。Zは、音響インピーダンスを示す。
振幅反射率 = |Z散乱体-Z媒体|/|Z散乱体+Z媒体|
エネルギー反射率 = |Z散乱体-Z媒体|2/|Z散乱体+Z媒体|2
続いて、本発明の実施の形態3について説明する。上述した実施の形態1では、基準ファントムからの超音波エコーに基づいた定数α、β、γ、α´、β´、γ´が超音波診断装置ではなくその外部で算出され、関係情報記憶部371に予め記憶されているものとして説明したが、本実施の形態3では、超音波診断システム1bが、定数α、β、γ、α´、β´、γ´を算出可能な構成をなす。図13は、本発明の実施の形態3に係る超音波診断装置を備えた超音波診断システムの構成を示すブロック図である。
続いて、本発明の実施の形態4について説明する。上述した実施の形態1では、関係情報記憶部371が、定数α、β、γ、α´、β´、γ´または関係式を予め記憶しているものとして説明したが、本実施の形態4では、関係情報記憶部371が、特徴量の値に応じて物理量を出力可能なルックアップテーブル(Lookup table:LUT)を記憶している。図14は、本発明の実施の形態4に係る超音波診断装置を備えた超音波診断システムの構成を示すブロック図である。
2 超音波内視鏡
3 超音波診断装置
4 表示装置
21 超音波振動子
31 送受信部
32 信号処理部
33 演算部
34 画像処理部
35 入力部
36 制御部
37 記憶部
38、334 変数変換部
39 重回帰分析部
201 特徴量画像
202 重畳画像表示部
203 情報表示部
331 周波数解析部
332 単回帰分析部
332a 近似部
332b 減衰補正部
333 推定部
341 Bモード画像データ生成部
342 物理量画像データ生成部
371 関係情報記憶部
Claims (16)
- 観測対象へ超音波を送信し、該観測対象で後方散乱された超音波を受信する超音波振動子を備えた超音波プローブが取得した超音波信号に基づいて超音波画像を生成する超音波診断装置であって、
前記観測対象から受信した超音波信号に基づき、特徴量を算出する特徴量算出部と、
含有する散乱体の物理量が既知の対照物体の前記物理量、および該対象物体から得られた特徴量に基づき導出された関係と、前記特徴量算出部が算出した前記観測対象の前記特徴量とを用いて、前記観測対象が含む散乱体の物理量を推定する推定部と、
前記推定部による推定結果を含み、表示部に表示させるための情報を生成する物理量情報生成部と、
を備えたことを特徴とする超音波診断装置。 - 前記物理量は、前記対照物体が含有する散乱体の数密度、前記散乱体の大きさ、および前記散乱体の散乱強度の少なくとも1つを含む、
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記物理量は、前記対照物体が含有する散乱体の散乱強度を含み、
前記散乱強度は、前記散乱体と媒体の振幅反射率、エネルギー反射率、および/または、それらの関数である
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記推定部は、前記特徴量算出部が算出した前記特徴量を、前記関係としての関係式に代入することにより前記観測対象が含む散乱体の物理量を推定する
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記関係式、該関係式の係数、該関係式の定数項、および前記関係を記述したテーブルのうちの少なくとも一つを記憶する関係情報記憶部をさらに備え、
前記推定部は、前記関係情報記憶部を参照して前記観測対象が含む散乱体の物理量を推定する
ことを特徴とする請求項4に記載の超音波診断装置。 - 前記関係式は、前記物理量および前記特徴量のうち少なくとも一部を重回帰分析することにより導出される
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記既知の散乱体の物理量のうち、前記散乱体の数密度、および前記散乱体の大きさを含む場合、
前記散乱体の数密度、および前記散乱体を非線形変換して前記重回帰分析を行う
ことを特徴とする請求項6に記載の超音波診断装置。 - 前記特徴量は、前記超音波信号をもとに算出される周波数特徴量を含む
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記特徴量は、前記超音波信号をもとに算出される減衰率を含む
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記特徴量は、前記超音波信号をもとに算出される音速を含む
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記物理量情報生成部は、前記推定部が推定した前記物理量に応じて視覚情報を付与した画像データを生成する
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記推定部が互いに異なる複数の物理量を推定した場合、
前記物理量情報生成部は、前記複数の物理量を同時、順次または異なるタイミングで前記表示部に表示される前記情報を生成する
ことを特徴とする請求項1に記載の超音波診断装置。 - 前記非線形変換が施された前記散乱体の数密度、および/または前記散乱体の大きさに対してさらに非線形変換を施す変数変換部
をさらに備えたことを特徴とする請求項6に記載の超音波診断装置。 - 前記観測対象から受信した超音波信号に基づき算出した特徴量において減衰の影響を補正する減衰補正部をさらに備え、
前記推定部が、前記含有する散乱体の物理量が既知の前記対照物体の前記物理量と、前記対照物体から得られた特徴量において減衰の影響を補正した値とに基づき導出された関係と、前記減衰補正部が補正した前記観測対象の前記特徴量の値とを用いて、前記観測対象が含む散乱体の物理量を推定する
ことを特徴とする請求項1に記載の超音波診断装置。 - 観測対象へ超音波を送信し、該観測対象で後方散乱された超音波を受信する超音波振動子を備えた超音波プローブが取得した超音波信号に基づいて超音波画像を生成する超音波診断装置の作動方法であって、
特徴量算出部が、前記観測対象から受信した超音波信号に基づき、特徴量を算出する特徴量算出ステップと、
推定部が、含有する散乱体の物理量が既知の対照物体の前記物理量、および該対象物体から得られた特徴量に基づき導出された関係と、前記特徴量算出部が算出した前記観測対象の前記特徴量とを用いて、前記観測対象が含む散乱体の物理量を推定する推定ステップと、
物理量情報生成部が、前記推定部による推定結果を含み、表示部に表示させるための情報を生成する物理量情報生成ステップと、
を含むことを特徴とする超音波診断装置の作動方法。 - 観測対象へ超音波を送信し、該観測対象で後方散乱された超音波を受信する超音波振動子を備えた超音波プローブが取得した超音波信号に基づいて超音波画像を生成する超音波診断装置の作動プログラムであって、
特徴量算出部が、前記観測対象から受信した超音波信号に基づき、特徴量を算出する特徴量算出手順と、
推定部が、含有する散乱体の物理量が既知の対照物体の前記物理量、および該対象物体から得られた特徴量に基づき導出された関係と、前記特徴量算出部が算出した前記観測対象の前記特徴量とを用いて、前記観測対象が含む散乱体の物理量を推定する推定手順と、
物理量情報生成部が、前記推定部による推定結果を含み、表示部に表示させるための情報を生成する物理量情報生成手順と、
を前記超音波診断装置に実行させることを特徴とする超音波診断装置の作動プログラム。
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