CN112294361A

CN112294361A - Ultrasonic imaging equipment and method for generating section image of pelvic floor

Info

Publication number: CN112294361A
Application number: CN201910684058.5A
Authority: CN
Inventors: 邹耀贤; 韩笑; 林穆清; 陈志杰; 龚闻达
Original assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd
Current assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd
Priority date: 2019-07-26
Filing date: 2019-07-26
Publication date: 2021-02-02

Abstract

The invention provides an ultrasonic imaging device and a method for generating a section image of a pelvic floor, which are characterized in that three-dimensional volume data of the pelvic floor are firstly obtained; identifying at least one critical anatomical structure associated with the location of the target tissue from the three-dimensional volumetric data; or generating at least one two-dimensional slice according to the prior position of the key anatomical structure associated with the position of the target tissue in the three-dimensional volume data, and identifying at least one key anatomical structure associated with the position of the target tissue from the two-dimensional slice; obtaining the spatial position of the key anatomical structure in the three-dimensional volume data; and imaging the section of the target tissue by taking the position of the key anatomical structure in the three-dimensional volume data as a basis to obtain a section image of the target tissue. Therefore, the ultrasonic doctor can obtain the section image of the pelvic floor target tissue only by completing the three-dimensional volume data acquisition of the pelvic floor, the operation is simple and convenient, and the work efficiency of the ultrasonic doctor is improved.

Description

Ultrasonic imaging equipment and method for generating section image of pelvic floor

Technical Field

The invention relates to the field of medical instruments, in particular to an ultrasonic imaging device and a method for generating a section image of a pelvic floor.

Background

In modern medical image examination, the ultrasonic technology has become the examination means which has the widest application and the highest use frequency and is the fastest when a new technology is popularized and applied due to the advantages of high reliability, rapidness, convenience, real-time imaging, repeatable examination and the like. The development of some new ultrasonic technologies, especially based on artificial intelligence auxiliary technologies, further promotes the application of the ultrasonic technologies in clinical diagnosis and treatment. Particularly in China, the population aging is more severe in recent years, and the population base is larger, so that the hospital ultrasonic examination faces increasingly vigorous patient requirements. The corresponding medical conditions are yet to be further improved, such as unbalanced distribution of medical resources between regions, great improvement of technical capability of primary doctors, and the like. The intelligent development of the ultrasonic equipment can help doctors to improve the examination efficiency, balance the difference of hospitals in different regions and provide more accurate diagnosis and personalized treatment schemes for patients.

Pelvic floor dysfunction such as stress urinary incontinence, pelvic organ prolapse and the like is one of common chronic diseases affecting physical and mental health of women, and seriously affects work and social activities of women. Ultrasonic examination of the pelvic floor plays an important role in diagnosing pelvic floor diseases, and by means of the current-stage ultrasonic technology, an ultrasonic clinician can dynamically observe changes of Valsalva motions and anus contracting motions of pelvic organs and levator ani fissures. Under the conventional two-dimensional condition, the anatomical structure and the prolapse condition of the visceral organs at the pelvic floor can be dynamically displayed in real time, and the prolapse condition can be quantitatively evaluated by a measuring ultrasonic clinician; under the three-dimensional/four-dimensional condition, the coronal plane of the minimum fissure hole section of the levator ani can be displayed, and whether the levator ani is injured or not can be observed layer by imaging a plurality of parallel sections of the fissure hole of the levator ani at the bottom of the ultrasonic basin in the state of anus contraction. The probe is rotated by 90 degrees and is inclined backwards and downwards, so that the cross section of the anal canal can be completely displayed, and whether the levator ani muscle is injured or not and whether the periphery of the levator ani muscle is diseased or not can be observed. Meanwhile, the measurement of the area of the levator ani fissure and the thickness of the puborectalis muscle under the three-dimensional/four-dimensional condition can help doctors to quantitatively evaluate the injury degree of the pelvic floor levator ani muscle.

However, when a doctor carries out ultrasonic diagnosis of the pelvic floor, the acquisition of the standard section and the imaging of the plurality of parallel sections need to be completed manually by the doctor, the process has high requirements on the experience and the manipulation of the doctor, and is time-consuming and labor-consuming, and meanwhile, the measurement process of related measurement items is extremely complicated. Meanwhile, the patient is difficult to complete and maintain Valsalva and anus contracting actions in the examination process, and a doctor is required to complete the imaging of a plurality of parallel sections more accurately and quickly. After the minimal fissure hole section of the levator ani and the parallel section corresponding to the fissure hole of the levator ani and the cross section of the anal canal are manually obtained, an ultrasonic clinician needs to manually measure various data, and the examination time and the examination efficiency of the clinician are greatly consumed.

Disclosure of Invention

The invention mainly provides an ultrasonic imaging device and a method for generating a tangent plane image of a pelvic floor, so as to improve the working efficiency of an ultrasonic doctor.

In one embodiment, a method for generating a tangent plane image of a pelvic floor is provided, and the method comprises the following steps:

acquiring three-dimensional volume data of the basin bottom;

identifying pubis symphysis and anorectal angle from the three-dimensional volume data, and obtaining the spatial positions of the pubis symphysis and the anorectal angle in the three-dimensional volume data;

determining the position of the minimum dehiscence hole tangent plane of levator ani muscles in the three-dimensional volume data based on the spatial positions of the pubis symphysis and the anorectal angle in the three-dimensional volume data;

and obtaining an image of the minimal fissure hole section of the levator ani according to the three-dimensional volume data based on the position of the minimal fissure hole section of the levator ani.

In one embodiment, identifying a pubic symphysis and an anorectal angle from the three-dimensional volumetric data, and obtaining the spatial location of the pubic symphysis and the anorectal angle in the three-dimensional volumetric data comprises:

identifying a pubis symphysis lower edge, two pubis rami and an anorectal angle from the three-dimensional volume data to obtain spatial positions of the pubis symphysis lower edge, the two pubis rami and the anorectal angle in the three-dimensional volume data;

determining the position of the levator ani minimum cleft tangent plane in the three-dimensional volume data based on the spatial position of the pubic symphysis and the anorectal angle in the three-dimensional volume data comprises:

and determining a tangent plane which passes through at least one part of the pubis combined lower edge and the anorectal horn and is parallel to a connecting line of two points which are symmetrical relative to the pubis combined lower edge on the two pubis branches according to the spatial positions of the pubis combined lower edge, the two pubis branches and the anorectal horn in the three-dimensional volume data, and taking the position of the tangent plane as the position of the minimum fissure hole tangent plane of the levator ani muscle.

identifying a pubis symphysis lower edge and an anorectal angle from the three-dimensional volume data, and obtaining the spatial positions of the pubis symphysis lower edge and the anorectal angle in the three-dimensional volume data;

determining a plurality of tangent planes passing through a predetermined point on the pubis combined lower edge and the anorectal angle according to the spatial positions of the pubis combined lower edge and the anorectal angle in the three-dimensional volume data, and obtaining tangent plane images of the tangent planes according to the three-dimensional volume data;

and determining the symmetry of image areas positioned at two sides of a connecting line of the pubis combined lower edge and the predetermined point in each section image of the section images of the plurality of sections, and determining the position of the section image with the symmetry meeting the predetermined condition as the position of the minimum fissure section of the levator ani muscle.

In one embodiment, the method further comprises: measuring the area of the minimum fissure hole of the levator ani according to the obtained section image of the minimum fissure hole of the levator ani; and/or detecting levator ani muscles and a urethral orifice in the minimum fissure section image of the levator ani muscles, and measuring the distance from the urethral orifice to the leftmost levator ani muscle and/or the distance from the urethral orifice to the rightmost levator ani muscle according to the detected levator ani muscles and urethral orifice; and/or extracting the outline of the levator ani muscle or the minimum fissure of the levator ani muscle from the section image of the minimum fissure of the levator ani muscle, and calculating the distance between the upper radial line and the lower radial line of the levator ani muscle and/or the distance between the left radial line and the right radial line of the levator ani muscle according to the outline.

In one embodiment, identifying a pubic symphysis from the three-dimensional volumetric data comprises: calculating at least one characteristic index of the three-dimensional volume data, and inputting the characteristic index into a pre-established model function of the corresponding relation between the characteristic index of the three-dimensional volume data and the pubic symphysis to obtain the corresponding pubic symphysis; or carrying out target detection or image segmentation on the three-dimensional volume data, carrying out morphological feature detection on each region obtained after detection or segmentation to obtain a plurality of candidate regions, judging that each candidate region is pubic symphysis according to the shape feature and/or the gray feature, and determining the candidate region with the highest probability as the pubic symphysis.

In one embodiment, identifying the anorectal angle from the three dimensional volumetric data comprises: calculating at least one characteristic index of the three-dimensional volume data, and inputting the characteristic index into a model function of a pre-established corresponding relation between the characteristic index of the three-dimensional volume data and the anorectal angle to obtain a corresponding anorectal angle; or carrying out target detection or image segmentation on the three-dimensional volume data, carrying out morphological feature detection on each region obtained after detection or segmentation to obtain a plurality of candidate regions, judging the probability that each candidate region is the anorectal angle according to the shape feature and/or the gray feature of each candidate region, and determining the candidate region with the highest probability as the anorectal angle.

In one embodiment, obtaining an image of the levator ani minimum fissure tangent plane from the three-dimensional volume data based on the position of the levator ani minimum fissure tangent plane comprises: based on the position of the minimum fissure hole section of the levator ani, obtaining image data containing the minimum fissure hole section of the levator ani from the three-dimensional volume data, and performing volume rendering on the image data containing the minimum fissure hole section to obtain a volume rendering image of the minimum fissure hole section; and/or obtaining a two-dimensional image of the levator minimum fissure hole section from the three-dimensional volume data based on the position of the levator ani minimum fissure hole section; and/or carrying out thick-layer imaging on the minimal fissure hole section of the levator ani according to the preset imaging thickness to obtain a thick-layer image of the minimal fissure hole section of the levator ani.

In one embodiment, a method for generating a tangent plane image of a pelvic floor is provided, which includes:

acquiring three-dimensional volume data of the basin bottom;

identifying at least one key anatomical structure associated with the position of the target tissue from the three-dimensional volume data and obtaining the spatial position of the key anatomical structure in the three-dimensional volume data; or generating at least one two-dimensional section according to the prior position of the key anatomical structure associated with the position of the target tissue in the three-dimensional volume data, identifying at least one key anatomical structure associated with the position of the target tissue from the two-dimensional section, and obtaining the spatial position of the key anatomical structure in the three-dimensional volume data;

and imaging the section of the target tissue by taking the position of the key anatomical structure in the three-dimensional volume data as a basis to obtain a section image of the target tissue.

In one embodiment, the target tissue is levator ani, the method further comprising:

detecting the levator ani based on the section image of the levator ani, and measuring the detected minimum fissure hole area of the levator ani;

or detecting the levator ani and the urethral orifice based on the tangent plane image of the levator ani, and measuring the distance from the urethral orifice to the leftmost levator ani and the distance from the urethral orifice to the rightmost levator ani.

In one embodiment, the target tissue is an anal canal, and the sectional image of the target tissue is an anal canal cross section; the method further comprises the following steps:

and detecting the puborectalis based on the anal canal transverse surface, and measuring the thickness of the detected puborectalis.

In one embodiment, identifying at least one critical anatomical structure associated with the location of the target tissue from the three-dimensional volumetric data comprises:

and calculating at least one characteristic index of the three-dimensional volume data, and inputting the characteristic index into a model function of the corresponding relation between the characteristic index of the three-dimensional volume data and the key anatomical structure, which is established in advance, to obtain the corresponding key anatomical structure.

and performing image segmentation on the three-dimensional volume data, performing morphological feature detection on each region obtained after the segmentation to obtain a plurality of candidate regions, judging the probability that each candidate region is a key anatomical structure according to the shape feature and/or the gray feature of each candidate region, and determining the candidate region with the highest probability as the key anatomical structure.

In one embodiment, generating at least one two-dimensional slice from a priori locations in the three-dimensional volume data of critical anatomical structures associated with the location of the target tissue, identifying at least one critical anatomical structure associated with the location of the target tissue from the two-dimensional slices comprises:

detecting a pair of most similar two-dimensional slices on both sides of a prior position of a key anatomical structure associated with the position of the target tissue in the three-dimensional volume data according to the prior position, and identifying the key anatomical structure from a central plane of the pair of two-dimensional slices.

In one embodiment, imaging the slice of the target tissue, and obtaining the slice image of the target tissue includes:

performing volume rendering imaging on the section of the target tissue to obtain a volume rendering image of the section of the target tissue; and/or the presence of a gas in the gas,

carrying out gray level imaging on the section of the target tissue to obtain a gray level image of the section of the target tissue; and/or the presence of a gas in the gas,

determining a reference line according to an input instruction of a user, sectioning and imaging the key anatomical structure through the reference line to obtain a section image of a target tissue; and/or the presence of a gas in the gas,

imaging the section of the target tissue to obtain images of a plurality of parallel sections of the target tissue; and/or the presence of a gas in the gas,

and according to the preset imaging thickness, carrying out thick-layer imaging on the section of the target tissue to obtain a thick-layer image of the section of the target tissue.

In one embodiment, the critical anatomical structure is a target tissue or a tissue capable of locating a target tissue.

In one embodiment, there is provided an ultrasound imaging apparatus comprising:

the ultrasonic probe is used for transmitting ultrasonic waves to an object to be imaged so as to scan the object to be imaged and receiving ultrasonic echoes returned from the object to be imaged;

the transmitting/receiving circuit is used for controlling the ultrasonic probe to transmit ultrasonic waves to an object to be imaged and receive echoes of the ultrasonic waves;

the processor is used for carrying out 3D reconstruction according to the echo of the ultrasonic wave to obtain three-dimensional volume data of the object to be imaged; the object to be imaged comprises a pelvic floor;

the processor is further configured to identify at least one critical anatomical structure associated with a location of a target tissue from the three-dimensional volume data and obtain a spatial location of the critical anatomical structure in the three-dimensional volume data; or generating at least one two-dimensional section according to the prior position of the key anatomical structure associated with the position of the target tissue in the three-dimensional volume data, identifying at least one key anatomical structure associated with the position of the target tissue from the two-dimensional section, and obtaining the spatial position of the key anatomical structure in the three-dimensional volume data; imaging the section of the target tissue by taking the position of the key anatomical structure in the three-dimensional volume data as a basis to obtain a section image of the target tissue;

and the display is used for displaying the section image of the target tissue.

In an ultrasound imaging apparatus in one embodiment, the target tissue is levator ani, and the processor is further configured to:

In the ultrasonic imaging device in one embodiment, the target tissue is an anal canal, and the section image of the target tissue is a cross section of the anal canal; the processor is further configured to:

In an ultrasound imaging apparatus in one embodiment, the processor identifying at least one critical anatomical structure associated with the location of the target tissue from the three-dimensional volume data comprises:

In the ultrasound imaging apparatus in one embodiment, the processor generates at least one two-dimensional slice from a priori positions in the three-dimensional volume data of critical anatomical structures associated with the position of the target tissue, and identifying at least one critical anatomical structure associated with the position of the target tissue from the two-dimensional slices includes:

In an embodiment of the ultrasound imaging apparatus, the imaging the slice of the target tissue by the processor, and obtaining the slice image of the target tissue includes:

In an ultrasound imaging apparatus in one embodiment, the critical anatomical structure is a target tissue or a tissue capable of locating a target tissue.

a memory for storing a program;

a processor for executing the program stored by the memory to implement the method as described above.

In one embodiment, a computer readable storage medium is provided, comprising a program executable by a processor to implement a method as described above.

According to the ultrasonic imaging device and the method for generating the section image of the pelvic floor of the embodiment, the three-dimensional volume data of the pelvic floor is acquired firstly; identifying at least one key anatomical structure associated with the position of the target tissue from the three-dimensional volume data and obtaining the spatial position of the key anatomical structure in the three-dimensional volume data; or generating at least one two-dimensional section according to the prior position of the key anatomical structure associated with the position of the target tissue in the three-dimensional volume data, identifying at least one key anatomical structure associated with the position of the target tissue from the two-dimensional section, and obtaining the spatial position of the key anatomical structure in the three-dimensional volume data; and imaging the section of the target tissue by taking the position of the key anatomical structure in the three-dimensional volume data as a basis to obtain a section image of the target tissue. Therefore, the ultrasonic doctor can obtain the section image of the pelvic floor target tissue only by completing the three-dimensional volume data acquisition of the pelvic floor, the operation is simple and convenient, and the work efficiency of the ultrasonic doctor is improved.

Drawings

FIG. 1 is a block diagram of an ultrasound imaging apparatus according to an embodiment;

FIG. 2 is a flow diagram of a method for generating a slice image of a basin bottom in one embodiment;

FIG. 3 is an ultrasound image of a sagittal section of the basin;

FIG. 4 is an effect diagram of volume rendering imaging of a minimal fissure foramen section of levator ani muscle;

FIG. 5 is an image of the effect of any section of the minimal fissure foramen section of levator ani muscle;

FIG. 6 is an image of the effect of imaging multiple parallel sections of the minimum dehiscence hole section of levator ani muscle;

fig. 7 is a schematic representation of a sectional image of the levator ani muscle minimum cleft in one embodiment.

Detailed Description

The present invention will be described in further detail with reference to the following detailed description and accompanying drawings. Wherein like elements in different embodiments are numbered with like associated elements. In the following description, numerous details are set forth in order to provide a better understanding of the present application. However, those skilled in the art will readily recognize that some of the features may be omitted or replaced with other elements, materials, methods in different instances. In some instances, certain operations related to the present application have not been shown or described in detail in order to avoid obscuring the core of the present application from excessive description, and it is not necessary for those skilled in the art to describe these operations in detail, so that they may be fully understood from the description in the specification and the general knowledge in the art.

Furthermore, the features, operations, or characteristics described in the specification may be combined in any suitable manner to form various embodiments. Also, the various steps or actions in the method descriptions may be transposed or transposed in order, as will be apparent to one of ordinary skill in the art. Thus, the various sequences in the specification and drawings are for the purpose of describing certain embodiments only and are not intended to imply a required sequence unless otherwise indicated where such sequence must be followed.

The numbering of the components as such, e.g., "first", "second", etc., is used herein only to distinguish the objects as described, and does not have any sequential or technical meaning. The term "connected" and "coupled" when used in this application, unless otherwise indicated, includes both direct and indirect connections (couplings).

The invention obtains three-dimensional volume data of the basin bottom; automatically detecting and identifying key anatomical structures in the three-dimensional volumetric data of the pelvic floor; based on the key anatomical structure, realizing automatic imaging of the pelvic floor, and based on the automatic imaging result of the pelvic floor, measuring; finally, displaying the imaging result and the automatic measurement result through a display; therefore, automatic imaging and automatic measurement of the disc bottom section image are realized, and the working efficiency of an ultrasonic doctor is improved. The three-dimensional volume data may be three-dimensional volume data generated by an ultrasound imaging apparatus, three-dimensional volume data generated by a nuclear magnetic resonance apparatus, or three-dimensional volume data generated by an electronic Computed Tomography (CT) acquisition. The ultrasound imaging apparatus and the method for generating a slice image of the pelvic floor thereof will be described in detail below by taking the ultrasound imaging apparatus as an example.

As shown in fig. 1, the ultrasound imaging apparatus provided by the present invention includes an ultrasound probe 30, a transmitting/receiving circuit 40 (i.e., a transmitting circuit 410 and a receiving circuit 420), a beam forming module 50, an IQ demodulation module 60, a processor 20, a human-computer interaction device 70, and a memory 80.

The ultrasonic probe 30 includes a transducer (not shown) composed of a plurality of array elements arranged in an array, the plurality of array elements are arranged in a row to form a linear array, or are arranged in a two-dimensional matrix to form an area array, and the plurality of array elements may also form a convex array. The array elements are used for emitting ultrasonic beams according to the excitation electric signals or converting the received ultrasonic beams into electric signals. Each array element can thus be used to perform a mutual transformation of the electrical impulse signal and the ultrasound beam, thus performing an emission of ultrasound waves towards the object to be imaged (e.g. the pelvic floor of a human body in this embodiment) and also an echo reception of ultrasound waves reflected back through the tissue. In performing ultrasonic testing, which array elements are used for transmitting ultrasonic beams and which array elements are used for receiving ultrasonic beams can be controlled by the transmitting circuit 410 and the receiving circuit 420, or the array elements are controlled to be time-slotted for transmitting ultrasonic beams or receiving echoes of ultrasonic beams. The array elements participating in ultrasonic wave transmission can be simultaneously excited by the electric signals, so that the ultrasonic waves are transmitted simultaneously; or the array elements participating in the ultrasonic wave transmission can be excited by a plurality of electric signals with certain time intervals, so that the ultrasonic waves with certain time intervals are continuously transmitted.

The array elements, for example, using piezoelectric crystals, convert the electrical signals into ultrasound signals according to the transmit sequence transmitted by transmit circuitry 410, which may include one or more scan pulses, one or more reference pulses, one or more push pulses, and/or one or more doppler pulses, depending on the application. The ultrasonic signal includes a focused wave and a plane wave according to the morphology of the wave.

The user selects a suitable position and angle by moving the ultrasonic probe 30 to transmit ultrasonic waves to the object 10 to be imaged and receive echoes of the ultrasonic waves returned by the object 10 to be imaged, and outputs ultrasonic echo signals, wherein the ultrasonic echo signals are channel analog electric signals formed by taking the receiving array elements as channels and carry amplitude information, frequency information and time information.

The transmit circuit 410 is configured to generate a transmit sequence according to the control of the processor 20, the transmit sequence being configured to control some or all of the plurality of array elements to transmit ultrasonic waves to the biological tissue, and parameters of the transmit sequence including the position of the array element for transmission, the number of array elements, and ultrasonic beam transmission parameters (e.g., amplitude, frequency, number of transmissions, transmission interval, transmission angle, wave pattern, focusing position, etc.). In some cases, the transmit circuitry 410 is further configured to phase delay the transmitted beams to cause different transmit elements to transmit ultrasound at different times so that each transmitted ultrasound beam can be focused at a predetermined region of interest. In different operation modes, such as a B image mode, a C image mode, and a D image mode (doppler mode), the parameters of the transmit sequence may be different, and the echo signals received by the receiving circuit 420 and processed by the subsequent modules and corresponding algorithms may generate a B image reflecting the tissue anatomy, a C image reflecting the tissue anatomy and blood flow information, and a D image reflecting the doppler spectrum image.

The receiving circuit 420 is configured to receive the ultrasonic echo signal from the ultrasonic probe 30 and process the ultrasonic echo signal. The receive circuit 420 may include one or more amplifiers, analog-to-digital converters (ADCs), and the like. The amplifier is used for amplifying the received echo signal after proper gain compensation, the amplifier is used for sampling the analog echo signal according to a preset time interval so as to convert the analog echo signal into a digitized signal, and the digitized echo signal still retains amplitude information, frequency information and phase information. The data output by the receiving circuit 420 may be output to the beamforming module 50 for processing or to the memory 80 for storage.

The beam forming module 50 is connected to the receiving circuit 420 for performing beam forming processing such as corresponding delay and weighted summation on the echo signal, because distances from the ultrasonic receiving point in the measured tissue to the receiving array elements are different, channel data of the same receiving point output by different receiving array elements have delay difference, delay processing is required, phases are aligned, and weighted summation is performed on different channel data of the same receiving point to obtain ultrasonic image data after beam forming, and the ultrasonic image data output by the beam forming module 50 is also referred to as radio frequency data (RF data). The beam synthesis module 50 outputs the radio frequency data to the IQ demodulation module 60. In some embodiments, the beam forming module 50 may also output the rf data to the memory 80 for buffering or saving, or directly output the rf data to the processor 20 for image processing.

Beamforming module 50 may perform the above functions in hardware, firmware, or software, for example, beamforming module 50 may include a central controller Circuit (CPU), one or more microprocessor chips, or any other electronic components capable of processing input data according to specific logic instructions, which when implemented in software, may execute instructions stored on a tangible and non-transitory computer readable medium (e.g., memory) to perform beamforming calculations using any suitable beamforming method.

The IQ demodulation module 60 removes the signal carrier by IQ demodulation, extracts the tissue structure information included in the signal, and performs filtering to remove noise, and the signal obtained at this time is referred to as a baseband signal (IQ data pair). The IQ demodulation module 60 outputs the IQ data pair to the processor 20 for image processing.

In some embodiments, the IQ demodulation module 60 further buffers or saves the IQ data pair output to the memory 80, so that the processor 20 reads the data from the memory 80 for subsequent image processing.

The IQ demodulation module 60 may also perform the above functions in hardware, firmware or software, and in some embodiments, the IQ demodulation module 60 may also be integrated with the beam synthesis module 50 in a single chip.

The processor 20 is used for a central controller Circuit (CPU), one or more microprocessors, a graphics controller circuit (GPU) or any other electronic components configured to process input data according to specific logic instructions, and may control peripheral electronic components according to the input instructions or predetermined instructions, or perform data reading and/or saving on the memory 80, or may process input data by executing programs in the memory 80, such as performing one or more processing operations on acquired ultrasound data according to one or more working modes, the processing operations including, but not limited to, adjusting or defining the form of ultrasound waves emitted by the ultrasound probe 30, generating various image frames for display by a display of the subsequent human-computer interaction device 70, or adjusting or defining the content and form of display on the display, or adjusting one or more image display settings (e.g., ultrasound images, graphics processing data, etc.) displayed on the display, Interface components, locating regions of interest).

The acquired ultrasound data may be processed by the processor 20 in real time during a scan or treatment as echo signals are received, or may be temporarily stored on the memory 80 and processed in near real time in an online or offline operation.

In this embodiment, the processor 20 controls the operations of the transmitting circuit 410 and the receiving circuit 420, for example, controls the transmitting circuit 410 and the receiving circuit 420 to operate alternately or simultaneously. The processor 20 may also determine an appropriate operation mode according to the selection of the user or the setting of the program, form a transmission sequence corresponding to the current operation mode, and send the transmission sequence to the transmitting circuit 410, so that the transmitting circuit 410 controls the ultrasound probe 30 to transmit the ultrasound wave using the appropriate transmission sequence.

The processor 20 is also operative to process the ultrasound data to generate a gray scale image of the signal intensity variations over the scan range, which reflects the anatomical structure inside the tissue, referred to as a B-image. The processor 20 may output the B image to a display of the human-computer interaction device 70 for display.

The human-computer interaction device 70 is used for human-computer interaction, namely receiving input and output visual information of a user; the input of the user can be received by a keyboard, an operating button, a mouse, a track ball and the like, and a touch screen integrated with a display can also be adopted; the display can be used for outputting visual information.

Based on the ultrasonic imaging device shown in fig. 1, the flow of generating the sectional image of the pelvic floor is shown in fig. 2, and includes the following steps:

step 1, the processor 20 performs 3D reconstruction according to the ultrasound data stored in the memory 80, or performs 3D reconstruction according to the ultrasound data output by the beam forming module 50, or performs 3D reconstruction according to the ultrasound data output by the IQ demodulation module 60, obtains three-dimensional volume data (three-dimensional volume data) of the pelvic floor, and outputs the three-dimensional volume data to the display of the human-computer interaction device 70 for display.

Step 2, the processor 20 identifies key anatomical structures from the three-dimensional volumetric data. In this embodiment, the target tissue is levator ani, and the key anatomical structure associated therewith may be the target tissue itself, or may be a tissue capable of positioning the target tissue, and in this embodiment, there may be two key anatomical structures associated therewith: the pubic symphysis inferior border (or its surrounding tissue), and the anorectal angle. The identification of the key anatomical structure of the pelvic floor can be an independent coordinate point for the lower edge point after pubic symphysis, and can also include/or an anatomical structure around the lower edge point after pubic symphysis (such as the pubic ramus structure of the lower edge point after pubic symphysis.

Wherein, the direct identification mode is shown in step 2.1 and comprises the following steps:

the processor 20 identifies at least one critical anatomical structure associated with the location of the target tissue from the three-dimensional volumetric data and obtains a spatial location of the critical anatomical structure in the three-dimensional volumetric data. In particular, the detection of key anatomical structures can be realized based on machine learning or deep learning methods. For example, at least one characteristic index of the three-dimensional volume data is calculated, and the characteristic index is input into a model function of a corresponding relation between the characteristic index of the three-dimensional volume data and the key anatomical structure, which is established in advance, so as to obtain the corresponding key anatomical structure. The method mainly comprises the following steps:

constructing a database: the database typically contains a plurality of sets of three-dimensional volume data of the ultrasound pelvic floor and calibration results of critical anatomical structures. The calibration result may be set according to actual task requirements, and may be an ROI (region of interest) frame containing a target, or a Mask (Mask) for accurately segmenting the posterior border (or/and surrounding tissues) of pubic symphysis and the anorectal corner region.

Positioning and identifying: after the database is built, the characteristics or rules of a target region (a key anatomical structure region) and a non-target region (a background region) in the database can be distinguished by a machine learning algorithm to realize the positioning and identification of the image. The implementation steps include, but are not limited to, the following cases.

The first case may employ a traditional sliding window based approach, in common form: firstly, extracting the features of the area in the sliding window, wherein the feature extraction method can be traditional PCA, LDA, Haar features, texture features and the like, and can also be a deep neural network for feature extraction, then matching the extracted features with a database, classifying by discriminators such as KNN, SVM, random forest, neural network and the like, and determining whether the current sliding window is the region of interest and acquiring the corresponding category of the region of interest.

In the second case, the detection and identification can be performed by using a Bounding-Box method based on deep learning, and the common form is as follows: the constructed database is subjected to feature learning and parameter regression by stacking the base layer convolution layer and the full connection layer, a corresponding Bounding-Box of the region of interest can be directly regressed through a network for an input image, and the category of the organization structure in the region of interest can be obtained at the same time, wherein common networks include R-CNN, Fast-RCNN, SSD, YOLO and the like.

The third situation is an end-to-end semantic segmentation network method based on deep learning, which is similar to the structure of the second Bounding-Box based on deep learning, and is different in that a full connection layer is removed, and an up-sampling or anti-convolution layer is added to enable the input size and the output size to be the same, so that an interested area and a corresponding category of an input image are directly obtained, and common networks include FCN, U-Net, Mask R-CNN and the like.

And in the fourth situation, the target is positioned only by adopting the method in the first situation, the method in the second situation or the method in the third situation, and then a classifier is additionally designed according to the positioning result to perform classification judgment on the target. The common classification judgment method comprises the following steps: firstly, feature extraction is carried out on a target ROI or Mask, the feature extraction method can be traditional PCA, LDA, Haar features, texture features and the like, and also can adopt a deep neural network to carry out feature extraction, then the extracted features are matched with a database, and classification is carried out by discriminators such as KNN, SVM, random forest, neural network and the like.

The positions of key anatomical structures such as the lower edge, the anorectal angle and the like after pubic symphysis in the three-dimensional volume data can be automatically positioned through the machine learning or depth learning algorithm, so that a standard minimal fissure area tangent plane of levator ani muscle can be conveniently positioned subsequently and used as the basis for subsequent imaging.

In the ultrasonic pelvic floor volume data, if the bilateral pubic ramus are parallel and symmetrical, the symmetry plane corresponding to the pubic ramus is the standard median sagittal section, as shown in fig. 3. After determination of the median sagittal section, the echo and surrounding tissues of the symphysis pubis and anorectal angle show significant differences: the pubic symphysis presents a high-brightness ellipse, the peripubic ramus fascia is high-brightness tissue wrapping the outer edge of the fascia, and the lower edge of the combined pubic symphysis is positioned at the intersection of the midline of the pubic ramus and the fascia; the anorectal angle assumes an angle when the subject is in different states of action (resting, contracting the anus and valsalva) and this angle is generally not greater than 180 °. Therefore, the detection of the pubis symphysis posterior margin and the anorectal angle can be realized by adopting a traditional characteristic detection method such as gray scale and/or morphology. For example, image segmentation is performed on three-dimensional volume data, specifically binary segmentation is performed, morphological feature detection is performed on each region obtained after the segmentation to obtain a plurality of candidate regions, then the probability that each candidate region is a key anatomical structure (pubic symphysis lower edge and anorectal angle) is judged according to shape features and/or gray features for each candidate region, and the candidate region with the highest probability is determined as the key anatomical structure. Of course, other conventional gray level detection and segmentation methods, such as the Otsu Threshold (OTSU), level set (LevelSet), Graph Cut (Graph Cut), Snake, etc., may also be used.

The indirect identification mode is shown in step 2.2: the processor 20 generates at least one two-dimensional slice from the a-priori positions in the three-dimensional volume data of the critical anatomical structures associated with the position of the target tissue, identifies at least one critical anatomical structure associated with the position of the target tissue from the two-dimensional slices, and obtains spatial positions of the critical anatomical structures in the three-dimensional volume data. In particular, the processor 20 detects a pair of two-dimensional slices on either side of a prior location based on the prior location in the three-dimensional volumetric data of a critical anatomical structure associated with the location of the target tissue, and identifies the critical anatomical structure from a central plane of the pair of two-dimensional slices. In particular, in this embodiment, the processor 20 detects a pair of two-dimensional slices on either side of the sagittal slice, based on the sagittal slice of the pelvic floor, and identifies the pubic symphysis posterior border and the anorectal angle from the central plane of the pair of two-dimensional slices. If the mid-sagittal section is directly identified, the ideal mid-sagittal section cannot be accurately found due to the problem of identification precision; the invention can accurately identify the key anatomical structure by searching symmetry without finding the midsagittal section,

the above-described method of identifying critical anatomical structures is automatic, but may, of course, be performed manually. Manually acquiring the anatomical structure is that a user informs the type and the position of a key structure of equipment through a keyboard, a mouse and other tools based on a certain workflow on a point, a line and the like on a specific anatomical structure in the three-dimensional volume data.

In one embodiment, when identifying the critical anatomical structure, the pubic symphysis inferior border, the two pubic ramis, and the anorectal angle may be identified directly from the three-dimensional volumetric data, thereby obtaining the spatial location of the pubic symphysis inferior border, the two pubic ramis, and the anorectal angle in the three-dimensional volumetric data. Then, according to the spatial position of the pubis symphysis inferior border, the two pubis rami and the anorectal angle in the three-dimensional volume data, a section passing through at least a part of the pubis symphysis inferior border and the anorectal angle and being parallel to a connecting line of two points on the two pubis rami symmetrical relative to the pubis symphysis inferior border is determined, namely the section is regarded as the minimum fissure incision section of the levator ani muscle, so that the position of the section can be taken as the position of the minimum fissure incision section of the levator ani muscle.

In one embodiment, when identifying critical anatomical structures, the pubic symphysis inferior border and the anorectal angle may be identified directly from the three-dimensional volumetric data to obtain spatial locations of the pubic symphysis inferior border and the anorectal angle in the three-dimensional volumetric data. Then, according to the spatial position of the pubis combined lower edge and the anorectal angle in the three-dimensional volume data, a plurality of sections passing through a connecting line of the pubis combined lower edge and a predetermined point on the anorectal angle are determined, and section images of the sections are obtained according to the three-dimensional volume data. Then, according to the image data of the section images of the plurality of sections, the symmetry of image areas (all or part of image areas) located on two sides of the connecting line of the lower edge of the pubis symphysis and the predetermined point in each section image is determined, and the section of the section image with the symmetry meeting the predetermined condition is regarded as the minimum fissure hole section of the levator ani, so that the position of the section image with the symmetry meeting the predetermined condition can be determined as the position of the minimum fissure hole section of the levator ani. Here, the "predetermined condition" may be set according to actual conditions. For example, in one embodiment, the predetermined condition may be set to "maximum symmetry". In another embodiment, the predetermined condition may be set such that the symmetry is greater than a certain value, the symmetry is less than a certain value, or the symmetry is within a certain range, or the like. The method for determining the symmetry of the image region may use a conventional method, and will not be described herein.

And 3, imaging the section of the target tissue by the processor 20 according to the position of the key anatomical structure in the three-dimensional volume data to obtain a section image of the target tissue, and displaying the section image of the target tissue through the display. For example, after identifying the inferior pubic symphysis margin and the anorectal angle in FIG. 3, the three-dimensional volumetric data is sectioned using a plane that intersects the plane of FIG. 3 through the inferior pubic symphysis margin and the anorectal angle, as indicated by the line in FIG. 3, to obtain the desired minimum dehiscence zone of the levator ani muscle. The sectional image of the target tissue can be presented in a volume rendering imaging mode, a section imaging mode, an arbitrary section (plane or curved surface) imaging mode, a multi-parallel plane imaging and section imaging mode, an arbitrary section (plane or curved surface) imaging mode and a combined mode of a plurality of parallel plane imaging and thick layer imaging.

Volume rendering imaging is to adjust the position and size of a Volume of Interest (VOI) and the curvature of an imaging curve based on key anatomical structures detected in three-dimensional Volume data, so as to display a levator ani fissure rendering image. The profile imaging is to generate an image of the levator ani fissure opening profile based on the position in space of the key anatomical adjustment profile detected in the three-dimensional volume data. The imaging of any section (plane or curved surface) is to generate a reference line (straight line or curve) based on a key anatomical structure detected in the three-dimensional volume data, and obtain a minimum fissure hole section of the levator ani muscle through the reference line; the imaging of multiple parallel planes is based on the detected key anatomical part, and the imaging of multiple parallel sections is realized at equal intervals by taking the minimum fissure area section of levator ani as a reference.

The effect of the processor 20 on volume rendering imaging of the levator ani minimum fissure area slice is shown in fig. 4. For three-dimensional imaging, volume rendering imaging is to display three-dimensional volume data in the VOI frame a through different imaging modes by adopting algorithms such as ray tracing and the like. The acquisition of a good volume rendered imaging map requires setting the size and position of the VOI box a in addition to the orientation of the volume data. To three-dimensional volume data of ultrasonic pelvic floor, detect anatomical structures such as pubis union and anus rectum angle after, can unite back lower edge and the specific position of anus rectum angle according to the pubis, automatically regulated body data position for the pubis unites back lower edge and anus rectum angle department in same horizontal position, VOI formation of image curve coincides with the pubis union lower edge and the straight line that anus rectum angle place as far as possible. Meanwhile, the VOI frame a is adjusted to a proper size (generally 2.5mm), and then the minimum fissure hole tangent plane of the levator ani muscle can be rendered, as shown in the lower right corner of fig. 5.

The processor 20 performs gray scale imaging on the minimum fissure area section of the levator ani muscle: the sectional image refers to a sectional image at a specific position and direction in the three-dimensional volume data, and sectional images at different positions and directions can be obtained by adjusting rotation and translation. Based on anatomical structures such as pubis combined lower edge and anorectal angle detected in the three-dimensional volume data, the standard tangent plane of minimum fissure area of levator ani muscle can be directly obtained through planar imaging. Usually, the minimum fissure incision plane of the levator ani is a two-dimensional incision plane passing through the lower pubic symphysis margin and the anorectal angle, so that a plane can be generated by detecting the key anatomical structure position in the three-dimensional volume data in the previous step, and the plane passes through (or approximately passes through) the incision plane where the lower pubic symphysis margin and the anorectal angle are located. The plane equation can be obtained by solving the equation or fitting, and after the plane equation is obtained, the gray-scale image corresponding to the plane can be taken out from the three-dimensional volume data, so that the minimal fissure area tangent plane of the levator ani muscle is obtained. On the basis of automatic imaging, the user can also finely adjust the tangent plane position of the levator ani fissure hole manually based on the positions of the pubis combined lower edge and the anorectal angle in the three-dimensional volume data.

The processor 20 performs automatic imaging of any section on the minimal fissure area section of the levator ani muscle: the minimal fissure hole section of the levator ani muscle can be displayed by using any section imaging besides a volume rendering imaging graph reconstructed by three-dimensional reconstruction, and the specific representation form is shown in fig. 5. In the imaging of an arbitrary section, one or more reference lines (straight lines or curved lines, straight lines in fig. 5) are taken from a certain section of the three-dimensional volume data, the reference lines and the three-dimensional data form a section (plane or curved surface), and the section is taken out and straightened into a plane for displaying. Generally, the minimum fissure incision of the levator ani muscle is formed by placing the reference line at the straight line formed by the lower pubic symphysis margin and the anorectal angle. After key anatomical structures such as the pubis combined lower edge, the anorectal angle and the like are obtained through the automatic identification method, the imaging straight line can be placed on the straight line formed by the two anatomical positions, and automatic imaging of any section of the minimum fissure hole of the levator ani muscle is achieved. Of course, the minimum fissure area tangent plane of the levator ani muscle can also be obtained manually, for example, a reference line is determined according to an input instruction of a user, and the critical anatomical structure is cut and imaged through the reference line to obtain the minimum fissure area tangent plane of the levator ani muscle.

The processor 20 performs multi-parallel section automatic imaging on the minimum fissure area section of the levator ani muscle: during the course of an ultrasound clinical examination, it is often necessary for the ultrasound clinician to view the levator ani fissure area based on multiple parallel slices to obtain more comprehensive diagnostic information. The imaging of multiple parallel facets refers to an imaging mode that multiple parallel facets are displayed simultaneously, the distances between adjacent facets are equal, and the distance between parallel planes can be adjusted by a user. After key anatomical parts such as pubic symphysis, anorectal horn and the like are detected, the minimum fissure area tangent plane of the levator ani can be obtained by the automatic imaging method for the minimum fissure area tangent plane of the levator ani, and then the equidistant multi-tangent-plane parallel imaging is performed on the levator ani by taking the tangent plane as a reference, as shown in fig. 6. The user can change the position of the reference section or reselect the reference section according to the actual situation. Meanwhile, the distance between the frames can be fixed and equal, and can also be automatically or manually adjusted according to the actual situation.

The processor 20 combines the above section imaging, arbitrary section imaging, multiple parallel section imaging and thick layer imaging respectively into an image: besides the four methods, the imaging mode of the levator ani fissure hole section can also combine three imaging modes of section imaging, arbitrary section imaging and imaging of a plurality of parallel sections with thick layer imaging. The thick layer imaging means that a certain thickness is added to the tomographic gray scale image and the tomographic gray scale image is displayed by a surface mode, an X-ray mode or a fusion mode of the surface mode and the X-ray mode. Wherein the thickness may be a preset imaging thickness. This mode can effectively improve the contrast resolution of the image, enhancing the display for critical anatomical structures and features, but attenuating image details. Meanwhile, the thickness of the thick-layer imaging image can be set to be a fixed value (such as 2.5mm) according to actual clinical requirements, or the thickness parameter can be adjusted in a self-adaptive manner according to actual anatomical structures and characteristics, and of course, a user can manually set the parameter based on personal requirements and operation habits.

During ultrasonic scanning, after the area section of the minimum fissure hole of the levator ani is scanned, the ultrasonic probe is rotated by 90 degrees and is inclined backwards and downwards, so that the cross section of the anal canal can be completely displayed. Therefore, after the processor 20 obtains the minimum fissure area tangent plane of the levator ani muscle, a tangent plane image of the anal canal cross section can be generated based on the position relationship between the anal canal cross section and the minimum fissure area tangent plane of the levator ani muscle. Of course, the target tissue may also be set as the anal canal, and the process of obtaining the section image of the anal canal cross section by the above method is similar to the process of obtaining the section of the minimum fissure area of levator ani, so that the detailed description is omitted. The imaging method of the puborectal muscle section is consistent with the imaging method of the minimum fissure area section of the levator ani, namely after a key anatomical part related to the anal sphincter is detected, puborectal muscle imaging can be carried out in various modes, namely, the combination of automatic imaging of puborectal muscle section volume rendering, section imaging, any section (plane or curved surface) imaging, multi-parallel plane imaging machine section imaging, any section (plane or curved surface) imaging and multiple parallel plane imaging with thick layer imaging is respectively carried out.

For the condition that the image quality is poor and the position of the key anatomical structure detected by the algorithm has deviation, the user can also carry out modification operations such as moving, zooming, deleting and re-calibrating on the VOI area in the detected section or the imaging curve of any section through tools such as a keyboard, a mouse and the like, so that semi-automatic VOI imaging or imaging of any section is realized; for the imaging of the standard tangent plane corresponding to the pelvic floor and the imaging of a plurality of parallel tangent planes, the user can also adjust the tangent planes through a knob.

And 4, measuring the section image of the target tissue. After obtaining the minimum fissure hole section of the levator ani muscle, doctors usually need to perform related measurement items on the corresponding section so as to quantitatively evaluate the prolapsed and torn condition of the visceral organs at the pelvic floor. However, the items of the related measurement items are often complicated, the measurement process is time-consuming and labor-consuming, and meanwhile, the requirements on the experience and the manipulation of a doctor are high, so that the robustness and the accuracy of the measurement result are difficult to ensure. Therefore, based on the obtained basin bottom tangent plane, the realization of the intelligent measurement of the corresponding measurement item is very important.

Based on the minimum fissure hole section of the levator ani, two items which are conventionally required to be measured by ultrasonic clinicians at the present stage are the minimum fissure hole area of the levator ani and the distances from the urethral orifice to the leftmost levator ani and the rightmost levator ani. For the volume rendering imaging section, the section imaging section and any sectioning plane imaging section, the intelligent measurement of the two measurement items is only needed to be realized on a single-frame image; for imaging a plurality of parallel sections, it is necessary to satisfy the requirement of performing intelligent measurement on one or more frames of images, wherein the selection of the measurement frame and the frame number satisfies the requirement-based setting of a user, and the default setting is the middle continuous three-frame image of fig. 6.

Therefore, in this embodiment, step 4 includes: the processor 20 detects the levator ani muscle based on a section image (minimum fissure hole section) of the levator ani muscle, and performs area statistics on the detected levator ani muscle to obtain the minimum fissure hole area of the levator ani muscle; the levator ani and urethral orifice are detected based on the tangent plane image of the levator ani, and the distance from the urethral orifice to the leftmost levator ani and the distance from the urethral orifice to the rightmost levator ani are measured.

Specifically, the processor 20 identifies the target to be measured, such as levator ani, based on the traditional target segmentation methods such as gray scale and/or morphology, and then performs measurement: in the fissure section of levator ani, levator ani presents a highlight muscle fiber sound beam, and the ultrasonic imaging characteristics are obviously different from surrounding anatomical structures. Therefore, similar to the concept of detecting the key anatomical structures, the processor 20 detects and segments the levator ani muscle by using the conventional gray scale and/or morphological detection and segmentation methods. For example, firstly, the diaphorax levator anus slit section image is subjected to binarization segmentation, a plurality of candidate regions are obtained through some necessary morphological operations, then, the probability that each candidate region is levator ani muscle is judged according to the characteristics of shape, gray brightness and the like, and a region with the highest probability is selected as a target segmentation region. Of course, other conventional gray level detection and segmentation methods, such as the Otsu Threshold (OTSU), level set (LevelSet), Graph Cut (Graph Cut), Snake, etc., may also be used.

The processor 20 may also identify an object to be measured, such as levator ani, based on an object segmentation method such as machine learning or deep learning, and further perform measurement: in addition to the conventional image segmentation method, similar to the target detection method, segmentation of the levator ani can be realized based on a target segmentation method such as machine learning and deep learning. The segmentation method may refer to the third and fourth cases of the corresponding object detection method. That is to say, the levator ani can be directly segmented based on a deep learning end-to-end semantic segmentation network; the target can also be positioned based on end-to-end network segmentation, and then a classifier is additionally designed according to the positioning result to classify and interpret the target at a pixel level, so that the levator ani muscle segmentation is realized in two steps. These two concepts are similar to those of the object detection method, and are not described herein again.

After the levator ani is segmented, other measurement items can be calculated based on the levator ani fissure hole section. For example, the distance from the urethral orifice to the leftmost side of the levator ani, and the distance from the urethral orifice to the rightmost side of the levator ani. It should be noted that the automatic measurement of the measurement item requires the algorithm system to automatically detect the urethral orifice, and the automatic detection method is the same as the above automatic detection method of the key anatomical structure, which is not described herein again.

In one embodiment, the contour of the levator ani muscle or the minimum fissure of the levator ani muscle can be extracted from the section image of the minimum fissure of the levator ani muscle, and the distance between the upper radial line and the lower radial line of the levator ani muscle and/or the distance between the left radial line and the right radial line of the levator ani muscle can be calculated according to the contour. As shown in fig. 7, a is the extracted contour of levator ani or the minimum fissure of levator ani, B is the left and right radial lines of levator ani, and C is the upper and lower radial lines of levator ani. Here, the distance between the upper and lower radial lines may be the length of the upper and lower radial lines C, and the distance between the left and right radial lines may be the length of the left and right radial lines B.

In the embodiment where the target tissue is the anal canal, the sectional image of the target tissue is the anal canal cross-section. Processor 20 detects the puborectalis muscle based on the anal canal transection, measures the thickness of the detected puborectalis muscle. Specifically, processor 20 measures the thickness of the puborectal muscle based on multiple parallel sections of the puborectal muscle. The thickness is measured three times continuously in the corresponding peripheral area of the same frame image, and each measurement result is correspondingly displayed and averaged. The selection of the measurement frame, the frame number and the measurement times meets the requirement-based setting of a user, and the default is to take three measurement results of the intermediate frame. The embodiment that the target tissue is the anal canal, the automatic measurement process is similar to the levator ani embodiment, and only the detected objects are different, so the detailed description is omitted.

The measurement of the measurement items can be fully automatic or semi-automatic. Semi-automatic measurement is such that a user can set one or more input points on the corresponding interface, and the corresponding measurement result is obtained based on the input points. Meanwhile, for the condition that the image quality is poor and the measurement result obtained through the intelligent algorithm has deviation, the user can also perform modification operations such as deletion, modification, re-input and the like on the result through tools such as a keyboard, a mouse and the like.

And 5, displaying the section image of the target tissue and the measurement result thereof by the processor 20 through the display of the human-computer interaction device 70. The doctor may need to measure different target tissues, so a certain workflow may be preset, the function of selecting the target tissues by the doctor is integrated into the workflow for the doctor to freely select, and the image and the measurement result corresponding to the selected function are displayed on the display.

In conclusion, the ultrasonic imaging device and the method for generating the section image of the pelvic floor provided by the invention can automatically generate the section of the target tissue of the pelvic area, and can perform corresponding measurement, thereby greatly improving the working efficiency of an ultrasonic doctor.

Those skilled in the art will appreciate that all or part of the functions of the various methods in the above embodiments may be implemented by hardware, or may be implemented by computer programs. When all or part of the functions of the above embodiments are implemented by a computer program, the program may be stored in a computer-readable storage medium, and the storage medium may include: a read only memory, a random access memory, a magnetic disk, an optical disk, a hard disk, etc., and the program is executed by a computer to realize the above functions. For example, the program may be stored in a memory of the device, and when the program in the memory is executed by the processor, all or part of the functions described above may be implemented. In addition, when all or part of the functions in the above embodiments are implemented by a computer program, the program may be stored in a storage medium such as a server, another computer, a magnetic disk, an optical disk, a flash disk, or a removable hard disk, and may be downloaded or copied to a memory of a local device, or may be version-updated in a system of the local device, and when the program in the memory is executed by a processor, all or part of the functions in the above embodiments may be implemented.

Reference is made herein to various exemplary embodiments. However, those skilled in the art will recognize that changes and modifications may be made to the exemplary embodiments without departing from the scope hereof. For example, the various operational steps, as well as the components used to perform the operational steps, may be implemented in differing ways depending upon the particular application or consideration of any number of cost functions associated with operation of the system (e.g., one or more steps may be deleted, modified or incorporated into other steps).

Additionally, as will be appreciated by one skilled in the art, the principles herein may be reflected in a computer program product on a computer readable storage medium, which is pre-loaded with computer readable program code. Any tangible, non-transitory computer-readable storage medium may be used, including magnetic storage devices (hard disks, floppy disks, etc.), optical storage devices (CD-ROMs, DVDs, Blu Ray disks, etc.), flash memory, and/or the like. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including means for implementing the function specified. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified.

While the principles herein have been illustrated in various embodiments, many modifications of structure, arrangement, proportions, elements, materials, and components particularly adapted to specific environments and operative requirements may be employed without departing from the principles and scope of the present disclosure. The above modifications and other changes or modifications are intended to be included within the scope of this document.

The foregoing detailed description has been described with reference to various embodiments. However, one skilled in the art will recognize that various modifications and changes may be made without departing from the scope of the present disclosure. Accordingly, the disclosure is to be considered in an illustrative and not a restrictive sense, and all such modifications are intended to be included within the scope thereof. Also, advantages, other advantages, and solutions to problems have been described above with regard to various embodiments. However, the benefits, advantages, solutions to problems, and any element(s) that may cause any element(s) to occur or become more pronounced are not to be construed as a critical, required, or essential feature or element of any or all the claims. As used herein, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, system, article, or apparatus. Furthermore, the term "coupled," and any other variation thereof, as used herein, refers to a physical connection, an electrical connection, a magnetic connection, an optical connection, a communicative connection, a functional connection, and/or any other connection.

Those skilled in the art will recognize that many changes may be made to the details of the above-described embodiments without departing from the underlying principles of the invention. Accordingly, the scope of the invention should be determined from the following claims.

Claims

1. A method for generating a sectional image of a pelvic floor, comprising:

acquiring three-dimensional volume data of the basin bottom;

2. The method of claim 1, wherein:

identifying a pubis symphysis and an anorectal angle from the three-dimensional volumetric data, the obtaining spatial positions of the pubis symphysis and the anorectal angle in the three-dimensional volumetric data comprising:

3. The method of claim 1, wherein:

4. A method according to any one of claims 1 to 3, wherein the method further comprises:

measuring the area of the minimum fissure hole of the levator ani according to the obtained section image of the minimum fissure hole of the levator ani;

and/or

Detecting levator ani and urethral orifice in the minimum fissure section image of the levator ani, and measuring the distance from the urethral orifice to the leftmost levator ani and/or the distance from the urethral orifice to the rightmost levator ani according to the detected levator ani and urethral orifice;

and/or

And extracting the outline of the levator ani muscle or the minimum fissure of the levator ani muscle from the section image of the minimum fissure of the levator ani muscle, and calculating the distance between the upper radial line and the lower radial line of the levator ani muscle and/or the distance between the left radial line and the right radial line of the levator ani muscle according to the outline.

5. The method of any one of claims 1 to 4, wherein identifying a pubic symphysis from the three-dimensional volumetric data comprises:

calculating at least one characteristic index of the three-dimensional volume data, and inputting the characteristic index into a pre-established model function of the corresponding relation between the characteristic index of the three-dimensional volume data and the pubic symphysis to obtain the corresponding pubic symphysis; or

And carrying out target detection or image segmentation on the three-dimensional volume data, carrying out morphological feature detection on each region obtained after detection or segmentation to obtain a plurality of candidate regions, judging that each candidate region is pubic symphysis according to shape features and/or gray features, and determining the candidate region with the highest probability as the pubic symphysis.

6. A method according to any one of claims 1 to 5, wherein identifying an anorectal angle from the three dimensional volumetric data comprises:

calculating at least one characteristic index of the three-dimensional volume data, and inputting the characteristic index into a model function of a pre-established corresponding relation between the characteristic index of the three-dimensional volume data and the anorectal angle to obtain a corresponding anorectal angle; or

And carrying out target detection or image segmentation on the three-dimensional volume data, carrying out morphological feature detection on each region obtained after detection or segmentation to obtain a plurality of candidate regions, judging the probability that each candidate region is the anorectal angle according to the shape feature and/or the gray feature of each candidate region, and determining the candidate region with the highest probability as the anorectal angle.

7. The method of any one of claims 1 to 6, wherein obtaining an image of the levator ani minimum cleft cross-section from the three-dimensional volumetric data based on the position of the levator ani minimum cleft cross-section comprises:

based on the position of the minimum fissure hole section of the levator ani, obtaining image data containing the minimum fissure hole section of the levator ani from the three-dimensional volume data, and performing volume rendering on the image data containing the minimum fissure hole section to obtain a volume rendering image of the minimum fissure hole section; and/or the presence of a gas in the gas,

based on the position of the minimum dehiscence hole section of the levator ani, obtaining a two-dimensional image of the minimum dehiscence hole section of the levator from the three-dimensional volume data; and/or the presence of a gas in the gas,

and carrying out thick-layer imaging on the minimal fissure hole section of the levator ani according to the preset imaging thickness to obtain a thick-layer image of the minimal fissure hole section of the levator ani.

8. A method for generating a sectional image of a pelvic floor, comprising:

acquiring three-dimensional volume data of the basin bottom;

9. The method of claim 8, wherein the target tissue is levator ani, the method further comprising:

or detecting the levator ani and the urethral orifice based on the tangent plane image of the levator ani, and measuring the distance from the urethral orifice to the leftmost levator ani and the distance from the urethral orifice to the rightmost levator ani;

or extracting the outline of the levator ani muscle or the minimum fissure hole of the levator ani muscle based on the section image of the levator ani muscle, and calculating the distance between the upper radial line and the lower radial line of the levator ani muscle and/or the distance between the left radial line and the right radial line of the levator ani muscle according to the outline.

10. The method of claim 8, wherein the target tissue is an anal canal and the sectional image of the target tissue is an anal canal cross-section; the method further comprises the following steps:

11. The method of claim 8, wherein identifying at least one critical anatomical structure associated with a location of a target tissue from the three-dimensional volumetric data comprises:

12. The method of claim 8, wherein identifying at least one critical anatomical structure associated with a location of a target tissue from the three-dimensional volumetric data comprises:

and carrying out target detection or image segmentation on the three-dimensional volume data, carrying out morphological feature detection on each region obtained after detection or segmentation to obtain a plurality of candidate regions, judging the probability that each candidate region is a key anatomical structure according to the shape feature and/or the gray feature of each candidate region, and determining the candidate region with the highest probability as the key anatomical structure.

13. The method of claim 8, wherein generating at least one two-dimensional slice from a priori locations in the three-dimensional volume data of critical anatomical structures associated with the location of the target tissue, identifying at least one critical anatomical structure associated with the location of the target tissue from the two-dimensional slices comprises:

14. The method of claim 8, wherein imaging a slice of the target tissue to obtain an image of the slice of the target tissue comprises:

15. The method of claim 8, wherein the critical anatomical structure is a target tissue or a tissue capable of locating a target tissue.

16. An ultrasonic imaging apparatus characterized by comprising:

and the display is used for displaying the section image of the target tissue.

17. The ultrasonic imaging apparatus of claim 16, wherein the target tissue is levator ani, the processor further configured to:

18. The ultrasonic imaging apparatus of claim 16, wherein the target tissue is an anal canal and the sectional image of the target tissue is an anal canal cross section; the processor is further configured to:

19. The ultrasound imaging apparatus of claim 16, wherein the processor identifying at least one critical anatomical structure associated with the location of the target tissue from the three-dimensional volumetric data comprises:

20. The ultrasound imaging apparatus of claim 16, wherein the processor identifying at least one critical anatomical structure associated with the location of the target tissue from the three-dimensional volumetric data comprises:

21. The ultrasound imaging device of claim 16, wherein the processor generates at least one two-dimensional slice from a priori locations in the three-dimensional volume data of critical anatomical structures associated with the location of the target tissue, the identifying at least one critical anatomical structure associated with the location of the target tissue from the two-dimensional slices comprising:

22. The ultrasonic imaging apparatus of claim 16, wherein the processor images a slice of the target tissue, and obtaining a slice image of the target tissue comprises:

23. Ultrasound imaging device as claimed in claim 16, characterized in that the critical anatomical structure is a target tissue or a tissue in which a target tissue can be located.

24. An ultrasonic imaging apparatus characterized by comprising:

a memory for storing a program;

a processor for executing the memory-stored program to implement the method of any one of claims 1-8.

25. A computer-readable storage medium, comprising a program executable by a processor to implement the method of any one of claims 1-15.