CN115886878A - Elasticity measuring method and ultrasonic imaging apparatus - Google Patents
Elasticity measuring method and ultrasonic imaging apparatus Download PDFInfo
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- CN115886878A CN115886878A CN202111164631.3A CN202111164631A CN115886878A CN 115886878 A CN115886878 A CN 115886878A CN 202111164631 A CN202111164631 A CN 202111164631A CN 115886878 A CN115886878 A CN 115886878A
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Abstract
An elasticity measurement method and an ultrasonic imaging apparatus, the elasticity measurement method comprising: acquiring a contrast image and an elastic image of a target section of a target tissue; determining a first region of interest in the contrast image from the contrast image; determining a second region of interest corresponding to the first region of interest in the elasticity image according to the corresponding relation between the contrast image and the elasticity image; acquiring elasticity data of the second region of interest, and acquiring a first elasticity measurement result according to the elasticity data of the second region of interest; and displaying the contrast image and the elastic image of the target section, and displaying the first elastic measurement result. The method and the device for acquiring the elastic image have the advantages that the contrast image and the elastic image of the same target section are acquired, the measurement area of the elastic image is determined based on the contrast image, and the problem that the measurement area of the elastic image is difficult to determine is solved.
Description
Technical Field
The present application relates to the field of ultrasound imaging technology, and more particularly, to an elasticity measurement method and an ultrasound imaging apparatus.
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. Ultrasound is commonly used for non-invasive examination of lesion sites such as tumors. In which malignant tumors are often accompanied by an increase in hardness different from that of ordinary tissues, and therefore, doctors usually analyze the lesion site by quantitatively measuring the hardness of the tissues at the lesion site using an elastography technique.
In a conventional elasticity measurement process, for hardness measurement of a lesion position, a doctor usually outlines the boundary of a lesion region according to a gray-scale image corresponding to an elasticity image in a tracing manner, so as to determine a measurement range of the elasticity measurement and obtain a corresponding elasticity result. However, for the lesion position which is not obvious in the gray-scale image, it is difficult to identify the image boundary for tracing measurement, and the delineation of the lesion area is time-consuming and labor-consuming, which seriously affects the measurement efficiency.
Disclosure of Invention
In this summary, concepts in a simplified form are introduced that are further described in the detailed description. This summary of the application is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
An aspect of an embodiment of the present application provides an elasticity measurement method, where the method includes: acquiring a contrast image and an elastic image of a target section of a target tissue; determining a first region of interest in the contrast image from the contrast image; determining a second region of interest corresponding to the first region of interest in the elasticity image according to the corresponding relation between the contrast image and the elasticity image; acquiring elasticity data of the second region of interest, and acquiring a first elasticity measurement result according to the elasticity data of the second region of interest; and displaying the contrast image and the elastic image of the target section, and displaying the first elastic measurement result.
In one embodiment, the determining a first region of interest in the contrast image from the contrast image comprises: acquiring contrast intensity data corresponding to each pixel point on the contrast image; comparing the contrast intensity data with a preset threshold range; and determining a set of pixel points corresponding to the contrast intensity data within the preset threshold range as the first region of interest.
In one embodiment, the determining a first region of interest in the contrast image from the contrast image comprises: and inputting the contrast image into a pre-trained machine learning model, and acquiring the first region of interest output by the machine learning model.
In one embodiment, the determining a first region of interest in the contrast image from the contrast image comprises: and carrying out edge detection on the contrast image to obtain an edge position of the first region of interest.
In one embodiment, the acquiring the contrast image and the elasticity image of the target section of the target tissue includes: transmitting first ultrasonic waves to the target tissue, receiving echo signals of the first ultrasonic waves, and generating a multi-frame contrast image of the target tissue according to the echo signals of the first ultrasonic waves; determining a contrast image of the target section in the multi-frame contrast image, and obtaining a reference gray-scale image of the target section; transmitting a second ultrasonic wave to the target tissue, receiving an echo signal of the second ultrasonic wave, and generating a multi-frame real-time gray scale image of the target tissue according to the echo signal of the second ultrasonic wave; determining a real-time gray scale image of the target section from a plurality of frames of real-time gray scale images according to the matching degree of the real-time gray scale image and the reference gray scale image; and transmitting a third ultrasonic wave to the target section according to the real-time gray scale image of the target section, receiving an echo signal of the third ultrasonic wave, and obtaining an elastic image of the target section according to the echo signal of the third ultrasonic wave.
In one embodiment, the acquiring a contrast image and an elasticity image of a target section of a target tissue includes: transmitting a fourth ultrasonic wave to the target tissue, receiving an echo signal of the fourth ultrasonic wave, and generating a multi-frame elastic image of the target tissue according to the echo signal of the fourth ultrasonic wave; determining an elastic image of the target section in the multi-frame elastic images, and obtaining a reference gray-scale image of the target section; transmitting a fifth ultrasonic wave to the target tissue, receiving an echo signal of the fifth ultrasonic wave, and generating a multi-frame real-time gray scale image of the target tissue according to the echo signal of the fifth ultrasonic wave; determining a real-time gray scale image of the target section from a plurality of frames of real-time gray scale images according to the matching degree of the real-time gray scale image and the reference gray scale image; and transmitting a sixth ultrasonic wave to the target section according to the real-time gray scale image of the target section, receiving an echo signal of the sixth ultrasonic wave, and obtaining a contrast image of the target section according to the echo signal of the sixth ultrasonic wave.
In one embodiment, the method further comprises: and simultaneously displaying the reference gray scale image, the contrast image of the target section, the real-time gray scale image of the target section and the elastic image of the target section.
In one embodiment, the method further comprises: identifying a third region of interest in the real-time gray scale image of the target section; determining a fourth region of interest corresponding to the third region of interest in the elastic image according to the corresponding relation between the elastic image and the real-time gray scale image; acquiring elasticity data of the fourth region of interest, and acquiring a second elasticity measurement result according to the elasticity data of the fourth region of interest; displaying the second elasticity measurement result.
In one embodiment, the method further comprises: calculating a ratio of the first elasticity measurement to the second elasticity measurement and displaying the ratio.
In one embodiment, the method further comprises: determining an area of the second region of interest and an area of the fourth region of interest; and calculating the ratio of the area of the second interested area to the area of the fourth interested area, and displaying the ratio.
In one embodiment, the method further comprises: determining a fifth region of interest in the elasticity image from the elasticity image; determining an area of the fourth region of interest and an area of the fifth region of interest; and calculating the ratio of the area of the fourth interested area to the area of the fifth interested area, and displaying the ratio.
In one embodiment, the method further comprises: determining a fifth region of interest in the elasticity image from the elasticity image; determining an area of the second region of interest and an area of the fifth region of interest; and calculating the ratio of the area of the second interested area to the area of the fifth interested area, and displaying the ratio.
In one embodiment, the method further comprises: acquiring contrast intensity data of the first region of interest, obtaining a first contrast intensity measurement result according to the contrast intensity data of the first region of interest, and displaying the first contrast intensity measurement result.
In one embodiment, the method further comprises: obtaining a reference gray-scale image corresponding to the contrast image of the target section; identifying a sixth region of interest in the reference grayscale image; determining a seventh region of interest corresponding to the sixth region of interest in the contrast image according to the corresponding relation between the contrast image of the target section and the reference gray-scale image; and acquiring contrast intensity data of the seventh region of interest, acquiring a second contrast intensity measurement result according to the contrast intensity data of the seventh region of interest, and displaying the second contrast intensity measurement result.
In one embodiment, the method further comprises: calculating a ratio of the first contrast intensity measurement to the second contrast intensity measurement and displaying the ratio.
In one embodiment, the method further comprises: displaying an outline of the first region of interest on the contrast image and an outline of the second region of interest on the elasticity image.
In one embodiment, the method further comprises: receiving an instruction for editing the outline of the first region of interest, re-determining the first region of interest according to the instruction for editing the outline of the first region of interest, and re-determining the second region of interest according to the re-determined first region of interest; and/or receiving an instruction for editing the outline of the second region of interest, and re-determining the second region of interest according to the instruction for editing the outline of the second region of interest.
In one embodiment, the first region of interest and the second region of interest correspond to a lesion location of the target tissue.
Another aspect of the embodiments of the present application provides an ultrasound imaging apparatus, including: an ultrasonic probe; the transmitting circuit is used for exciting the ultrasonic probe to transmit ultrasonic waves to target tissues; the receiving circuit is used for controlling the ultrasonic probe to receive the echo of the ultrasonic wave so as to obtain an echo signal of the ultrasonic wave; a processor for performing the steps of the elasticity measurement method as described above.
The elasticity measurement method and the ultrasonic imaging equipment obtain the contrast image and the elasticity image of the same target tangent plane, determine the measurement area of the elasticity image based on the contrast image, and solve the problem that the measurement area of the elasticity image is difficult to determine.
Drawings
The above and other objects, features and advantages of the present application will become more apparent by describing in more detail embodiments of the present application with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings, like reference numbers generally represent like parts or steps.
FIG. 1 shows a block diagram of an ultrasound imaging device according to an embodiment of the present application;
FIG. 2 shows a schematic flow diagram of an elasticity measurement method according to an embodiment of the present application;
FIG. 3 is a schematic diagram illustrating simultaneous display of a reference grayscale image, a contrast image of a target slice, a real-time grayscale image of the target slice, and an elasticity image of the target slice according to one embodiment of the present application;
fig. 4A-4C show schematic diagrams of editing a second region of interest according to one embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, exemplary embodiments according to the present application will be described in detail below with reference to the accompanying drawings. It should be understood that the described embodiments are only some embodiments of the present application and not all embodiments of the present application, and that the present application is not limited by the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the application described in the application without inventive step, shall fall within the scope of protection of the application.
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present application. It will be apparent, however, to one skilled in the art, that the present application may be practiced without one or more of these specific details. In other instances, well-known features of the art have not been described in order to avoid obscuring the present application.
It is to be understood that the present application is capable of implementation in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term "and/or" includes any and all combinations of the associated listed items.
In order to provide a thorough understanding of the present application, a detailed structure will be provided in the following description in order to explain the technical solution proposed in the present application. Alternative embodiments of the present application are described in detail below, however, the present application may have other implementations in addition to these detailed descriptions.
Next, an ultrasound imaging apparatus according to an embodiment of the present application is first described with reference to fig. 1, and fig. 1 shows a schematic structural block diagram of an ultrasound imaging apparatus 100 according to an embodiment of the present application.
As shown in fig. 1, the ultrasound imaging apparatus 100 includes an ultrasound probe 110, a transmit circuit 112, a receive circuit 114, a processor 116, and a display 118. Further, the ultrasound imaging apparatus may further include a transmission/reception selection switch 120 and a beam forming module 122, and the transmission circuit 112 and the reception circuit 114 may be connected to the ultrasound probe 110 through the transmission/reception selection switch 120.
The ultrasonic probe 110 includes a plurality of transducer elements, which may be arranged in a line to form a linear array, or in a two-dimensional matrix to form an area array, or in a convex array. The transducer elements are used for transmitting ultrasonic waves according to the excitation electric signals or converting the received ultrasonic waves into electric signals, so that each transducer element can be used for realizing the mutual conversion of the electric pulse signals and the ultrasonic waves, thereby realizing the transmission of the ultrasonic waves to tissues of a target area of a measured object and also receiving ultrasonic wave echoes reflected back by the tissues. In ultrasound detection, which transducer elements are used for transmitting ultrasound waves and which transducer elements are used for receiving ultrasound waves can be controlled by a transmitting sequence and a receiving sequence, or the transducer elements are controlled to be time-slotted for transmitting ultrasound waves or receiving echoes of ultrasound waves. The transducer elements participating in the ultrasonic wave transmission can be simultaneously excited by the electric signals, so that the ultrasonic waves are transmitted simultaneously; alternatively, the transducer elements participating in the ultrasound beam transmission may be excited by several electrical signals with a certain time interval, so as to continuously transmit ultrasound waves with a certain time interval.
During ultrasound imaging, the processor 116 controls the transmit circuitry 112 to send the delay focused transmit pulses to the ultrasound probe 110 through the transmit/receive select switch 120. The ultrasonic probe 110 is excited by the transmission pulse to transmit an ultrasonic beam to a target tissue of a measured object, receives an ultrasonic echo with tissue information reflected from the target tissue after a certain time delay, and converts the ultrasonic echo back into an electrical signal again. The receiving circuit 114 receives the electrical signals generated by the ultrasound probe 110, obtains ultrasound echo signals, and sends the ultrasound echo signals to the beam forming module 122, and the beam forming module 122 performs processing such as focusing delay, weighting, and channel summation on the ultrasound echo data, and then sends the ultrasound echo data to the processor 116. The processor 116 performs signal detection, signal enhancement, data conversion, logarithmic compression, and the like on the ultrasonic echo signals to form an ultrasonic image. The ultrasound images obtained by the processor 116 may be displayed on the display 118 or may be stored in the memory 124.
Alternatively, the processor 116 may be implemented as software, hardware, firmware, or any combination thereof, and may use a single or multiple Application Specific Integrated Circuits (ASICs), a single or multiple general purpose Integrated circuits, a single or multiple microprocessors, a single or multiple programmable logic devices, or any combination of the foregoing, or other suitable circuits or devices. Also, the processor 116 may control other components in the ultrasound imaging apparatus 100 to perform the respective steps of the methods in the various embodiments herein.
The display 118 is connected with the processor 116, and the display 118 may be a touch display screen, a liquid crystal display screen, or the like; alternatively, the display 118 may be a separate display, such as a liquid crystal display, a television, or the like, separate from the ultrasound imaging apparatus 100; alternatively, the display 118 may be a display screen of an electronic device such as a smart phone, a tablet computer, and the like. The number of the displays 118 may be one or more.
The display 118 may display the ultrasound image obtained by the processor 116. In addition, the display 118 can provide a graphical interface for human-computer interaction for the user while displaying the ultrasound image, and one or more controlled objects are arranged on the graphical interface, so that the user can input operation instructions by using the human-computer interaction device to control the controlled objects, thereby executing corresponding control operation. For example, an icon is displayed on the graphical interface, and the icon can be operated by the man-machine interaction device to execute a specific function, such as drawing a region-of-interest box on the ultrasonic image.
Optionally, the ultrasound imaging apparatus 100 may further include a human-computer interaction device other than the display 118, which is connected to the processor 116, for example, the processor 116 may be connected to the human-computer interaction device through an external input/output port, which may be a wireless communication module, a wired communication module, or a combination thereof. The external input/output port may also be implemented based on USB, bus protocols such as CAN, and/or wired network protocols, etc.
The human-computer interaction device may include an input device for detecting input information of a user, for example, control instructions for the transmission/reception timing of the ultrasonic waves, operation input instructions for drawing points, lines, frames, or the like on the ultrasonic images, or other instruction types. The input device may include one or more of a keyboard, mouse, scroll wheel, trackball, mobile input device (e.g., mobile device with touch screen display, cell phone, etc.), multi-function knob, and the like. The human interaction means may also include an output device such as a printer.
It should be understood that the components included in the ultrasound imaging apparatus 100 shown in fig. 1 are merely illustrative and that more or fewer components may be included. This is not limited by the present application.
Next, an elasticity measurement method according to an embodiment of the present application will be described with reference to fig. 2. Fig. 2 is a schematic flow chart of an elasticity measurement method 200 according to an embodiment of the present application.
As shown in fig. 2, an elasticity measurement method 200 according to an embodiment of the present application includes the following steps:
in step S210, acquiring a contrast image and an elasticity image of a target section of a target tissue;
in step S220, determining a first region of interest in the contrast image according to the contrast image;
in step S230, determining a second region of interest corresponding to the first region of interest in the elasticity image according to the correspondence between the contrast image and the elasticity image;
in step S240, elasticity data of the second region of interest is obtained, and a first elasticity measurement result is obtained according to the elasticity data of the second region of interest;
in step S250, displaying the contrast image and the elasticity image of the target slice, and displaying the first elasticity measurement result.
The elasticity measurement method 200 of the embodiment of the application adopts a contrast elastography technology to obtain a contrast image and an elasticity image of the same target section, and the positions of interested areas such as a tumor area and the like can be determined based on blood flow perfusion information provided by the contrast image, so that the measurement area of the elasticity image is determined, the problem that the measurement area of the elasticity image cannot be determined based on only a gray scale image is avoided, and the accuracy and the measurement efficiency of elasticity measurement are improved.
Specifically, in step S210, a contrast image and an elasticity image of a target section of a target tissue are first acquired. In one embodiment, the target tissue is first imaged with contrast: the method comprises the steps of transmitting first ultrasonic waves to a target tissue, receiving echo signals of the first ultrasonic waves, generating a multi-frame contrast image of the target tissue according to the echo signals of the first ultrasonic waves, determining a contrast image of a target section in the multi-frame contrast image, and obtaining a reference gray-scale image of the target section. And then, transmitting a second ultrasonic wave to the target tissue, receiving an echo signal of the second ultrasonic wave, and generating a multi-frame real-time gray scale image of the target tissue according to the echo signal of the second ultrasonic wave. According to the matching degree of the real-time gray-scale image and the reference gray-scale image, the real-time gray-scale image of the target section can be determined from the multi-frame real-time gray-scale image. And finally, performing elastic imaging on the target tissue according to the real-time gray-scale image of the target section, transmitting a third ultrasonic wave to the target section, receiving an echo signal of the third ultrasonic wave, and obtaining an elastic image of the target section according to the echo signal of the third ultrasonic wave. By performing the above steps, a contrast image and an elastic image corresponding to the same object slice can be obtained.
Before the target tissue is subjected to contrast imaging, a contrast agent needs to be injected into the target tissue, an ultrasonic imaging mode is started, and a multi-frame contrast image and a corresponding gray-scale image are obtained. The contrast image shows the contrast intensity, and the contrast intensity shows the intensity of blood perfusion. The contrast agent microbubbles enhance the intensity of the reflected echoes, which can spread with the body's blood to various organs of the body. Because the blood vessels in the lesion areas such as tumors are active, the microbubble perfusion of the contrast agent is rich, so that the lesion areas can be clearly visualized in a contrast image. And selecting one frame of image with image characteristics capable of meeting the clinical observation requirement from the multi-frame contrast images, namely selecting the contrast image of the target section. In some embodiments, the contrast image corresponding to the time with the maximum contrast intensity may be selected as the contrast image of the target section, and the time with the maximum contrast intensity indicates that the blood perfusion at the current lesion position reaches the peak value, so as to better reflect the microcirculation state of the lesion position. When the reference gray-scale image of the target section is obtained, the gray-scale image corresponding to the target section may be extracted from the gray-scale image obtained when the contrast image is obtained, or after the contrast image corresponding to the target section is obtained, the gray-scale image of the target section is re-performed to obtain the gray-scale image of the target section.
And then, carrying out gray scale imaging on the target tissue in real time, and continuously acquiring multi-frame real-time gray scale images of the target tissue. And when the real-time gray-scale image is acquired, calculating the matching degree between each frame of real-time gray-scale image and the reference gray-scale image in real time, and acquiring the real-time gray-scale image corresponding to the target section according to the calculated matching degree. The matching degree can be calculated according to an image matching algorithm, a reference gray-scale image and a real-time gray-scale image can be displayed at the same time, and the matching degree is estimated subjectively by a user. And when the matching degree is higher than a preset threshold value, approximately considering that the current real-time gray-scale image and the reference gray-scale image correspond to the same tangent plane, and performing elastic imaging at the position and the posture of the ultrasonic probe corresponding to the current real-time gray-scale image to obtain an elastic image corresponding to the target tangent plane.
The elastic imaging of the embodiment of the application can be strain elastic imaging and also can be shear wave elastic imaging. The strain elastic imaging is mainly to apply pressure to a target tissue through a handheld ultrasonic probe, obtain ultrasonic echo signals before and after the target tissue is compressed, and calculate displacement of corresponding positions before and after the compression, namely the displacement information of the target tissue at two different moments. By solving the axial gradient of the displacement, the strain value of each point of the target tissue can be obtained, and the strain value is expressed in an image form, namely a strain elastic image. The strain elastic image can intuitively reflect the difference between hardness and softness or the difference between elasticity of different tissues, under the same external force compression, the larger the strain, the softer the tissue is, and the smaller the strain, the harder the tissue is. Shear wave elastography firstly excites focused ultrasonic beams through an ultrasonic probe to form acoustic radiation force, a shear wave source is formed in target tissues and transversely transmitted shear waves are generated, and the hardness difference of the target tissues can be obtained quantitatively and visually by identifying and detecting the shear waves generated in the tissues and the transmission parameters thereof and imaging the transmission parameters.
In another embodiment, in order to obtain the contrast image and the elasticity image of the target section of the target tissue, the elasticity image of the target section may be determined by performing elasticity imaging on the target tissue, and then the contrast image of the target section may be determined according to the matching result of the gray-scale image of the target section and the real-time gray-scale image. Specifically, a fourth ultrasonic wave is transmitted to the target tissue, an echo signal of the fourth ultrasonic wave is received, and a multi-frame elastic image of the target tissue is generated according to the echo signal of the fourth ultrasonic wave; and determining an elastic image of the target section in the multi-frame elastic image, and obtaining a reference gray-scale image of the target section. And then, transmitting a fifth ultrasonic wave to the target tissue, receiving an echo signal of the fifth ultrasonic wave, generating a multi-frame real-time gray-scale image of the target tissue according to the echo signal of the fifth ultrasonic wave, and determining a real-time gray-scale image of a target section from the multi-frame real-time gray-scale image according to the matching degree of the real-time gray-scale image and the reference gray-scale image. And finally, transmitting a sixth ultrasonic wave to the target section according to the real-time gray-scale image of the target section, receiving an echo signal of the sixth ultrasonic wave, and obtaining a contrast image of the target section according to the echo signal of the sixth ultrasonic wave.
Referring to fig. 3, after the contrast image and the elastic image of the target section of the target tissue are obtained, the reference grayscale image 301, the contrast image 302 of the target section, the real-time grayscale image 303 of the target section, and the elastic image 304 of the target section may be simultaneously displayed, so as to simultaneously present tissue structure information, blood flow microcirculation perfusion information, and elastic distribution information of the target section, thereby providing more comprehensive clinical information for a user.
In step S220, a first region of interest in the contrast image is determined from the contrast image. The first region of interest may correspond to a lesion location in the target tissue, for example where a tumor is located. For lesions that are partially not well visualized in the grayscale image, it is difficult to locate the lesion region through the grayscale image. However, on the contrast image, the blood supply of the lesion area is usually relatively rich, and it is obvious from the contrast image that the contrast signal intensity of the lesion area is significantly higher than that of the surrounding area. Therefore, whether the lesion area can be located by the gray-scale image or not, the position of the lesion area can be located by the blood flow supply information provided by the contrast image.
In one embodiment, the first region of interest may be determined from contrast intensity information contained in the contrast image. Specifically, contrast intensity data corresponding to each pixel point on a contrast image is obtained, the contrast intensity data corresponding to each pixel point is compared with a preset threshold range, and a set of pixel points corresponding to the contrast intensity data within the preset threshold range is determined as a first region of interest. The contrast intensity can reflect blood flow supply information, the first region of interest determined according to the contrast intensity data is a region corresponding to the tissue with unique blood flow supply characteristics, and particularly, the region corresponding to the tissue lesion position in the contrast image can be accurately positioned according to the contrast intensity data.
In other embodiments, the first region of interest may also be determined from image information contained in the contrast image. For example, the contrast image is input into a machine learning model trained in advance, and a first region of interest output by the machine learning model is acquired. When the machine learning model is trained, the characteristics of the pre-constructed database are learned by stacking the convolutional layers and the full connection layers, so that the first region of interest of the input image is directly obtained.
Alternatively, the contrast image may be subjected to edge detection to obtain the edge position of the first region of interest, i.e. the contour of the first region of interest. The edge detection detects all points with large gray value change in the contrast image, and the points are connected to form a plurality of lines, namely image edges. The edge detection algorithm comprises a Sobel edge detection algorithm, a Laplace edge detection algorithm, a Canny edge detection algorithm and the like.
After the first region of interest in the contrast image is determined, an outline of the first region of interest may be displayed on the contrast image to prompt the user for the shape, size, and location of the first region of interest.
In step S230, a second region of interest corresponding to the first region of interest is determined in the elasticity image according to the correspondence between the contrast image and the elasticity image. Since the elasticity image and the contrast image correspond to the same target slice, the position of the target tissue in the contrast image is the same as the position of the target tissue in the elasticity image, and the second region of interest, i.e., the region having the same shape, size and position as the first region of interest in the elasticity image. After the second region of interest in the elasticity image is determined, an outline of the second region of interest can be displayed in the elasticity image to prompt the user for the shape, size, and location of the second region of interest.
From the contours of the first region of interest displayed on the contrast image and the contours of the second region of interest displayed on the elasticity image, the user can assess that the automatically determined region of interest can conform to his perception of the target tissue. If the user considers that the automatically determined first region of interest and the second region of interest do not meet the requirements, the editing function can be started to edit the outline of the first region of interest. Specifically, the user may edit the first region of interest, the system may receive an instruction to edit the outline of the first region of interest, re-determine the first region of interest according to the instruction to edit the outline of the first region of interest, and re-determine the second region of interest according to the re-determined first region of interest. Or, the user may also edit the second region of interest, and the system receives an instruction to edit the outline of the second region of interest, and re-determines the second region of interest according to the instruction to edit the outline of the second region of interest.
Referring to fig. 4A-4C, fig. 4A-4C illustrate editing of a second region of interest. The user can draw a tracing line on the second region of interest, the tracing line replaces the contour line on the left side of the second region of interest, and the partial contour of the second region of interest is redefined, so that the correction of the contour of the second region of interest is realized. After editing the second region of interest, the first region of interest is also changed in synchronization therewith. Fig. 4A shows an outline of the second region of interest, fig. 4B shows a user-drawn trace, and fig. 4C shows the corrected second region of interest.
In some embodiments, the editing function may be started after the automatic measurement is completed, and the user may decide whether to re-edit the first region of interest or the second region of interest according to the shape, the position, or the internal image information of the first region of interest and the second region of interest, or may decide whether to re-edit the first region of interest or the second region of interest according to whether the measurement result is within an expected range.
Thereafter, in step S240, elasticity data of the second region of interest is obtained, and a first elasticity measurement result is obtained according to the elasticity data of the second region of interest. Because the elasticity image is generated based on the distribution of the elasticity data, the statistical operation can be performed on the elasticity data such as shear wave velocity, shear modulus or young modulus corresponding to each pixel point in the second region of interest to obtain the first elasticity measurement result. The first elasticity measurement includes, but is not limited to, statistics such as an average, a minimum, a maximum, a quartile value, or a standard deviation of the elasticity data of the second region of interest.
In some embodiments, the first elasticity measurement result may also be obtained statistically according to the elasticity data corresponding to the partial pixel points in the second region of interest, for example, a region to be measured with a predetermined size and a predetermined shape may be drawn inside the second region of interest, and the elasticity data inside the region to be measured may be counted to obtain the first elasticity measurement result. After the first elasticity measurement result is obtained, in step S250, a contrast image and an elasticity image of the target slice are displayed, and the first elasticity measurement result is displayed.
The second region of interest is determined from the contrast image, and in some embodiments, a region of interest in the elasticity image may be additionally determined from the grayscale image and measured, which is analyzed in comparison with the second region of interest and the first elasticity measurement determined from the contrast image. Specifically, a third interested area in the real-time gray-scale image of the target section is identified, and a fourth interested area corresponding to the third interested area is determined in the elastic image according to the corresponding relation between the elastic image and the real-time gray-scale image. The fourth region of interest is the region of interest determined from the grayscale image. And then, acquiring elasticity data of a fourth region of interest, and acquiring and displaying a second elasticity measurement result according to the elasticity data of the fourth region of interest. Typically, the second elasticity measurement should be close to the first elasticity measurement, and the user can evaluate the accuracy of the measurement based on the deviation between the two. In order to quantitatively reflect the deviation of the first elasticity measurement from the second elasticity measurement, a ratio of the first elasticity measurement to the second elasticity measurement may also be calculated and displayed.
In addition to the elasticity measurement result, since the fourth region of interest and the second region of interest correspond to the same target tissue, ideally, the fourth region of interest should be close to the second region of interest, so that the area of the second region of interest and the area of the fourth region of interest can be determined, the ratio of the area of the second region of interest to the area of the fourth region of interest can be calculated and displayed, and the user can automatically determine the accuracy of the region of interest according to the ratio evaluation system.
Since lesion regions such as tumors are also more obviously represented in the elasticity image, for example, malignant tumors are often accompanied by an increase in stiffness, in some embodiments, a region of interest may also be determined in the elasticity image according to the elasticity image itself for measurement, and the region of interest determined according to the elasticity image itself may be defined as a fifth region of interest. Then, the area of the fourth region of interest and the area of the fifth region of interest may be determined, and the ratio of the two areas may be calculated and displayed, or the area of the second region of interest and the area of the fifth region of interest may be determined, and the ratio of the two areas may be calculated and displayed. The first region of interest and the second region of interest are determined according to blood flow perfusion information provided by a contrast image, the third region of interest and the fourth region of interest are determined according to tissue structure information provided by a gray-scale image, the fifth region of interest is determined according to elasticity information provided by an elasticity image, and the ratio between the elasticity measurement result and the elasticity measurement result corresponding to the respective regions of interest and the ratio of the areas of different regions of interest are displayed, so that the user can comprehensively analyze target tissues.
Since a contrast image is also generated during the contrast elastography, in one embodiment, contrast intensity data of a first region of interest in the contrast image may also be acquired, and a first contrast intensity measurement is obtained and displayed based on the contrast intensity data of the first region of interest. The method of obtaining the first contrast intensity measurement result according to the contrast intensity data is similar to the method of obtaining the first elasticity measurement result according to the elasticity data, that is, statistics is performed according to the contrast intensity data corresponding to part or all of the pixel points in the first region of interest to obtain the first contrast intensity measurement result.
The first region of interest corresponding to the first contrast intensity measurement result is determined according to the contrast intensity, in some embodiments, a region of interest for contrast intensity measurement may be additionally determined according to the grayscale image, and a region of interest identified in the reference grayscale image corresponding to the contrast image may be defined as a sixth region of interest. After the sixth region of interest is determined, a seventh region of interest corresponding to the sixth region of interest is determined in the contrast image according to the correspondence between the contrast image and the reference grayscale image, contrast intensity data of the seventh region of interest is obtained, and a second contrast intensity measurement result is obtained and displayed according to the contrast intensity data of the seventh region of interest. Furthermore, the ratio of the first contrast intensity measurement result to the second contrast intensity measurement result can be calculated and displayed, and a judgment basis for the accuracy of the contrast intensity measurement result is provided for a user.
In summary, the elasticity measurement method 200 of the embodiment of the present application obtains the contrast image and the elasticity image of the same target tangent plane, and determines the measurement area of the elasticity image based on the contrast image, thereby solving the problem that the measurement area of the elasticity image is difficult to determine.
The embodiment of the present application further provides an ultrasonic imaging apparatus, which is used for implementing the elasticity measurement method 200. Referring back to fig. 1, the ultrasound imaging apparatus may be implemented as the ultrasound imaging apparatus 100 shown in fig. 1, the ultrasound imaging apparatus 100 may include an ultrasound probe 110, a transmitting circuit 112, a receiving circuit 114, a processor 116, and a display 118, optionally, the ultrasound imaging apparatus 100 may further include a transmitting/receiving selection switch 120 and a beam forming module 122, the transmitting circuit 112 and the receiving circuit 114 may be connected to the ultrasound probe 110 through the transmitting/receiving selection switch 120, and the description of each component may refer to the above description, which is not repeated here.
The transmitting circuit 112 is used for exciting the ultrasonic probe 110 to transmit ultrasonic waves to the target tissue; the receiving circuit 114 is configured to control the ultrasound probe 110 to receive an echo of the ultrasound wave to obtain an ultrasound echo signal; the processor 116 is configured to execute the above steps of the elasticity measurement method 200, and specifically includes: acquiring a contrast image and an elastic image of a target section of a target tissue; determining a first region of interest in the contrast image from the contrast image; determining a second region of interest corresponding to the first region of interest in the elastic image according to the corresponding relation between the contrast image and the elastic image; acquiring elasticity data of the second region of interest, and acquiring a first elasticity measurement result according to the elasticity data of the second region of interest; and displaying the contrast image and the elastic image of the target section, and displaying the first elastic measurement result.
Only the main functions of the components of the ultrasound imaging apparatus have been described above, and for more details, reference is made to the description of the elasticity measurement method 200. The ultrasonic imaging equipment of the embodiment of the application obtains the contrast image and the elastic image of the same target section, determines the measurement area of the elastic image based on the contrast image, and solves the problem that the measurement area of the elastic image is difficult to determine.
Although the example embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the above-described example embodiments are merely illustrative and are not intended to limit the scope of the present application thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present application. All such changes and modifications are intended to be included within the scope of the present application as claimed in the appended claims.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another device, or some features may be omitted, or not executed.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the description of exemplary embodiments of the present application, various features of the application are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the application and aiding in the understanding of one or more of the various inventive aspects. However, the method of the present application should not be construed to reflect the intent: this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which this invention pertains. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this application.
It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where such features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Moreover, those of skill in the art will understand that although some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the application and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some of the modules according to embodiments of the present application. The present application may also be embodied as apparatus programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present application may be stored on a computer readable medium or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The application may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
The above description is only for the specific embodiments of the present application or the description thereof, and the protection scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope disclosed in the present application, and shall be covered by the protection scope of the present application. The protection scope of the present application shall be subject to the protection scope of the claims.
Claims (19)
1. An elasticity measurement method, characterized in that the method comprises:
acquiring a contrast image and an elastic image of a target section of a target tissue;
determining a first region of interest in the contrast image from the contrast image;
determining a second region of interest corresponding to the first region of interest in the elasticity image according to the corresponding relation between the contrast image and the elasticity image;
acquiring elasticity data of the second region of interest, and acquiring a first elasticity measurement result according to the elasticity data of the second region of interest;
and displaying the contrast image and the elastic image of the target section, and displaying the first elastic measurement result.
2. The elasticity measurement method of claim 1, wherein said determining a first region of interest in the contrast image from the contrast image comprises:
acquiring contrast intensity data corresponding to each pixel point on the contrast image;
comparing the contrast intensity data with a preset threshold range;
and determining a set of pixel points corresponding to the contrast intensity data within the preset threshold range as the first region of interest.
3. The elasticity measurement method according to claim 1, wherein the determining a first region of interest in the contrast image from the contrast image comprises:
and inputting the contrast image into a pre-trained machine learning model, and acquiring the first region of interest output by the machine learning model.
4. The elasticity measurement method according to claim 1, wherein the determining a first region of interest in the contrast image from the contrast image comprises:
and carrying out edge detection on the contrast image to obtain an edge position of the first region of interest.
5. The elasticity measurement method according to claim 1, wherein the acquiring of the contrast image and the elasticity image of the target section of the target tissue comprises:
transmitting first ultrasonic waves to the target tissue, receiving echo signals of the first ultrasonic waves, and generating a multi-frame contrast image of the target tissue according to the echo signals of the first ultrasonic waves;
determining a contrast image of the target section in the multi-frame contrast image, and obtaining a reference gray-scale image of the target section;
transmitting a second ultrasonic wave to the target tissue, receiving an echo signal of the second ultrasonic wave, and generating a multi-frame real-time gray scale image of the target tissue according to the echo signal of the second ultrasonic wave;
determining a real-time gray scale image of the target section from a plurality of frames of real-time gray scale images according to the matching degree of the real-time gray scale image and the reference gray scale image;
and transmitting a third ultrasonic wave to the target section according to the real-time gray scale image of the target section, receiving an echo signal of the third ultrasonic wave, and obtaining an elastic image of the target section according to the echo signal of the third ultrasonic wave.
6. The elasticity measurement method according to claim 1, wherein the acquiring of the contrast image and the elasticity image of the target section of the target tissue comprises:
transmitting a fourth ultrasonic wave to the target tissue, receiving an echo signal of the fourth ultrasonic wave, and generating a multi-frame elastic image of the target tissue according to the echo signal of the fourth ultrasonic wave;
determining an elastic image of the target section in the multi-frame elastic image, and obtaining a reference gray-scale image of the target section;
transmitting a fifth ultrasonic wave to the target tissue, receiving an echo signal of the fifth ultrasonic wave, and generating a multi-frame real-time gray scale image of the target tissue according to the echo signal of the fifth ultrasonic wave;
determining a real-time gray scale image of the target tangent plane from a plurality of frames of real-time gray scale images according to the matching degree of the real-time gray scale image and the reference gray scale image;
and transmitting a sixth ultrasonic wave to the target section according to the real-time gray scale image of the target section, receiving an echo signal of the sixth ultrasonic wave, and obtaining a contrast image of the target section according to the echo signal of the sixth ultrasonic wave.
7. The elasticity measuring method according to claim 5 or 6, further comprising:
and simultaneously displaying the reference gray scale image, the contrast image of the target section, the real-time gray scale image of the target section and the elastic image of the target section.
8. The elasticity measuring method according to claim 5 or 6, further comprising:
identifying a third region of interest in the real-time gray scale image of the target section;
determining a fourth region of interest corresponding to the third region of interest in the elastic image according to the corresponding relation between the elastic image and the real-time gray scale image;
acquiring elasticity data of the fourth region of interest, and acquiring a second elasticity measurement result according to the elasticity data of the fourth region of interest;
displaying the second elasticity measurement.
9. The elasticity measuring method according to claim 8, further comprising:
calculating a ratio of the first elasticity measurement to the second elasticity measurement and displaying the ratio.
10. The elasticity measuring method according to claim 8, further comprising:
determining an area of the second region of interest and an area of the fourth region of interest;
and calculating the ratio of the area of the second interested area to the area of the fourth interested area, and displaying the ratio.
11. The elasticity measuring method according to claim 8, further comprising:
determining a fifth region of interest in the elasticity image from the elasticity image;
determining an area of the fourth region of interest and an area of the fifth region of interest;
and calculating the ratio of the area of the fourth interested area to the area of the fifth interested area, and displaying the ratio.
12. The elasticity measuring method according to claim 1, further comprising:
determining a fifth region of interest in the elasticity image from the elasticity image;
determining an area of the second region of interest and an area of the fifth region of interest;
and calculating the ratio of the area of the second interested area to the area of the fifth interested area, and displaying the ratio.
13. The elasticity measuring method according to claim 1, further comprising:
acquiring contrast intensity data of the first region of interest, obtaining a first contrast intensity measurement result according to the contrast intensity data of the first region of interest, and displaying the first contrast intensity measurement result.
14. The elasticity measuring method according to claim 13, further comprising:
obtaining a reference gray-scale image corresponding to the contrast image of the target section;
identifying a sixth region of interest in the reference grayscale image;
determining a seventh interested area corresponding to the sixth interested area in the contrast image according to the corresponding relation between the contrast image of the target section and the reference gray-scale image;
and acquiring contrast intensity data of the seventh region of interest, acquiring a second contrast intensity measurement result according to the contrast intensity data of the seventh region of interest, and displaying the second contrast intensity measurement result.
15. The elasticity measuring method according to claim 14, further comprising:
calculating a ratio of the first contrast intensity measurement to the second contrast intensity measurement and displaying the ratio.
16. The elasticity measuring method according to claim 1, further comprising:
displaying an outline of the first region of interest on the contrast image and an outline of the second region of interest on the elasticity image.
17. The elasticity measuring method according to claim 16, further comprising:
receiving an instruction for editing the outline of the first region of interest, re-determining the first region of interest according to the instruction for editing the outline of the first region of interest, and re-determining the second region of interest according to the re-determined first region of interest;
and/or receiving an instruction for editing the outline of the second region of interest, and re-determining the second region of interest according to the instruction for editing the outline of the second region of interest.
18. The elasticity measurement method of claim 1, wherein the first region of interest and the second region of interest correspond to a lesion location of the target tissue.
19. An ultrasound imaging apparatus, comprising:
an ultrasonic probe;
the transmitting circuit is used for exciting the ultrasonic probe to transmit ultrasonic waves to target tissues;
the receiving circuit is used for controlling the ultrasonic probe to receive the echo of the ultrasonic wave so as to obtain an echo signal of the ultrasonic wave;
a processor for performing the steps of the elasticity measurement method of any of claims 1-18.
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