Ultrasound contrast imaging method and ultrasound imaging system

Abstract

An ultrasound contrast imaging method and system are disclosed. The method includes: acquiring three-dimensional ultrasound data and three-dimensional contrast imaging data of a target tissue, wherein the target tissue contains a contrast agent; acquiring the location information of artifact regions in the three-dimensional ultrasound data; determining the location information of artifact regions in the three-dimensional contrast imaging data based on the location information of the artifact regions in the three-dimensional ultrasound data; rendering the three-dimensional contrast imaging data to obtain a rendered image, and processing the artifact regions during the rendering process to weaken or remove the artifact regions in the rendered image. This method solves the problem of aliasing interference on tissue structures caused by artifacts behind the contrast agent delivery tube in contrast images, which makes it impossible to distinguish artifacts from normal tissue structures in contrast images, thereby effectively improving the diagnostic accuracy of doctors.

Description

Technical Field

[0001] This invention relates to the field of ultrasound imaging technology, and more specifically to an ultrasound contrast imaging method and an ultrasound imaging system. Background Technology

[0002] For examining fallopian tube blockage, there are two common medical methods: hysterosalpingography (HSG) with iodized oil and hysterosalpingography (HSG) with ultrasound. HSG with iodized oil involves injecting a high-density iodine solution into the uterine cavity through the cervix, followed by X-ray imaging to visualize the uterine cavity. HSG with ultrasound, under three-dimensional ultrasound monitoring, observes in real-time the flow of the contrast agent through the uterine cavity and fallopian tubes, as well as its distribution in the pelvic cavity, to determine fallopian tube patency. It also allows for observation of the uterus, ovaries, and pelvic cavity. Both methods are equally accurate in assessing fallopian tube patency. However, compared to HSG with iodized oil, HSG with ultrasound offers advantages such as no radiation exposure, shorter post-operative preparation time for pregnancy, lower risk of contrast agent allergies, and greater convenience in observing uterine muscle tissue and follicles.

[0003] During hysterosalpingography (HSG), contrast agent is injected into the uterine cavity and fallopian tubes through a contrast agent delivery tube. Because the contrast agent delivery tube has relatively low acoustic attenuation, the posterior wall enhancement effect during ultrasound imaging causes artifacts to appear behind the contrast agent delivery tube in the HSG image. These artifacts overlap with normal tissue structures in the HSG image, making it virtually impossible to distinguish them from normal tissue structures based solely on the HSG image, severely impacting the doctor's diagnostic process. Summary of the Invention

[0004] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. The summary section of this invention is not intended to limit the key features and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0005] One embodiment of the present invention provides an ultrasound contrast imaging method, the method comprising:

[0006] Acquire three-dimensional ultrasound data and three-dimensional contrast imaging data of a target tissue, wherein the target tissue contains a contrast agent;

[0007] Obtain the location information of the artifact regions in the three-dimensional ultrasound data;

[0008] Based on the location information of the artifact regions in the three-dimensional ultrasound data, the location information of the artifact regions in the three-dimensional contrast imaging data is determined;

[0009] The three-dimensional imaging data is rendered to obtain a rendered image, and the artifact regions are processed during the rendering process to weaken or remove the artifact regions in the rendered image; or, the data corresponding to the artifact regions is weakened or removed from the three-dimensional imaging data, and the three-dimensional imaging data after removing the data corresponding to the artifact regions is rendered to obtain a rendered image.

[0010] A second aspect of the present invention provides an ultrasound imaging system, the ultrasound imaging system comprising:

[0011] Ultrasonic probe;

[0012] A transmitting circuit is used to control the ultrasound probe to emit ultrasound waves toward the target tissue containing the contrast agent;

[0013] A receiving circuit is used to receive the ultrasonic echo of the ultrasonic wave and obtain an ultrasonic echo signal;

[0014] The processor is used to acquire three-dimensional ultrasound data and three-dimensional contrast data of the target tissue based on the ultrasound echo signal;

[0015] Memory is used to store executable program instructions;

[0016] The processor is also configured to execute the program instructions stored in the memory, causing the processor to perform the aforementioned ultrasound contrast imaging method;

[0017] A monitor is used to display visual information.

[0018] According to the ultrasound contrast imaging method and system of the present invention, the method acquires the location information of artifact regions in the three-dimensional ultrasound data; determines the location information of artifact regions in the three-dimensional contrast imaging data based on the location information of artifact regions in the three-dimensional ultrasound data; renders the three-dimensional contrast imaging data to obtain a rendering image, and processes the artifact regions during the rendering process to weaken or remove the artifact regions in the rendering image; or, weakens or removes the data corresponding to the artifact regions from the three-dimensional contrast imaging data, and renders the three-dimensional contrast imaging data after removing the data corresponding to the artifact regions to obtain a rendering image. This solves the problem of aliasing interference on tissue structures caused by artifacts behind the contrast agent delivery tube in contrast images, which leads to the inability to distinguish between artifacts and normal tissue structures when observing contrast images, thereby effectively improving the diagnostic accuracy of doctors. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] In the attached diagram:

[0021] Figure 1 A schematic block diagram of an ultrasound imaging system according to an embodiment of the present invention is shown;

[0022] Figure 2 A schematic flowchart of an ultrasound contrast imaging method according to an embodiment of the present invention is shown;

[0023] Figure 3 A schematic diagram illustrating the indirect localization of artifacts in a two-dimensional section of three-dimensional B-mode data from hysterosalpingography according to an embodiment of the present invention is shown.

[0024] Figure 4 A comparison image before and after the removal of contrast artifacts is shown according to an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely a part of the embodiments of the present invention, and not all of the embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein. Based on the embodiments of the present invention described herein, all other embodiments obtained by those skilled in the art without inventive effort should fall within the protection scope of the present invention.

[0026] In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention can be practiced without one or more of these details. In other instances, certain technical features well-known in the art have not been described in order to avoid obscuring the invention.

[0027] It should be understood that the invention can be embodied in various forms and should not be construed as being limited to the embodiments set forth herein. Rather, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including,” when used in this specification, identify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0029] To fully understand this invention, a detailed structure will be presented in the following description to illustrate the technical solution proposed by this invention. Optional embodiments of the invention are described in detail below; however, in addition to these detailed descriptions, the invention may have other embodiments.

[0030] Below, first refer to Figure 1 An ultrasound imaging system according to an embodiment of the present invention is described. Figure 1 A schematic structural block diagram of an ultrasound imaging system 100 according to an embodiment of the present invention is shown.

[0031] like Figure 1 As shown, the ultrasound imaging system 100 includes an ultrasound probe 110, a transmitting circuit 112, a receiving circuit 114, a processor 116, and a display 118. Further, the ultrasound imaging system may also include a transmit / receive selection switch 120 and a beamforming module 122. The transmitting circuit 112 and the receiving circuit 114 can be connected to the ultrasound probe 110 via the transmit / receive selection switch 120.

[0032] The ultrasonic probe 110 includes multiple transducer elements. These elements can be arranged in a row to form a linear array, or in a two-dimensional matrix to form a planar array. They can also form a convex array. Each transducer element is used to emit ultrasonic waves based on an excitation electrical signal, or to convert received ultrasonic waves into electrical signals. Therefore, each transducer element can be used to achieve the mutual conversion between electrical pulse signals and ultrasonic waves, thereby enabling the emission of ultrasonic waves to the target area of ​​the object being tested, and also to receive ultrasonic wave echoes reflected back from the tissue. During ultrasonic testing, the transmission and reception sequences can be used to control which transducer elements are used to emit ultrasonic waves and which are used to receive ultrasonic waves, or to control the transducer elements to be used in time-slotted manner for emitting ultrasonic waves or receiving ultrasonic wave echoes. Transducer elements participating in ultrasonic wave emission can be simultaneously excited by electrical signals, thus emitting ultrasonic waves simultaneously; alternatively, transducer elements participating in ultrasonic beam emission can be excited by several electrical signals with a certain time interval, thus continuously emitting ultrasonic waves with a certain time interval.

[0033] During ultrasound imaging, the transmitting circuit 112 sends a delayed-focused transmission pulse to the ultrasound probe 110 via the transmit / receive selection switch 120. Excited by the transmission pulse, the ultrasound probe 110 emits an ultrasonic beam towards the tissue of the target area of ​​the object being measured. After a certain delay, it receives the ultrasonic echo reflecting back from the tissue of the target area, carrying tissue information, and converts this ultrasonic echo back into an electrical signal. The receiving circuit 114 receives the electrical signal converted by the ultrasound probe 110, obtains the ultrasonic echo signal, and sends these ultrasonic echo signals to the beamforming module 122. The beamforming module 122 performs focusing delay, weighting, and channel summation on the ultrasonic echo data, and then sends it to the processor 116. The processor 116 performs signal detection, signal enhancement, data conversion, and logarithmic compression on the ultrasonic echo signal to form an ultrasound image. The ultrasound image obtained by the processor 116 can be displayed on the display 118 or stored in the memory 124.

[0034] Optionally, the processor 116 can be implemented as software, hardware, firmware, or any combination thereof, and can use one or more application-specific integrated circuits (ASICs), one or more general-purpose integrated circuits, one or more microprocessors, one or more programmable logic devices, or any combination of the foregoing circuits and / or devices, or other suitable circuits or devices. Furthermore, the processor 116 can control other components in the ultrasound imaging system 100 to perform the corresponding steps of the methods in the various embodiments of this specification.

[0035] The display 118 is connected to the processor 116. The display 118 can be a touch screen, an LCD screen, etc.; or, the display 118 can be an independent display such as an LCD screen or a television, separate from the ultrasound imaging system 100; or, the display 118 can be the screen of an electronic device such as a smartphone or tablet, etc. The number of displays 118 can be one or more.

[0036] The display 118 can display the ultrasound images obtained by the processor 116. Furthermore, while displaying the ultrasound images, the display 118 can also provide a graphical user interface (HMI) for human-computer interaction. One or more controlled objects can be set on the HMI, allowing the user to input operation commands to control these controlled objects and perform corresponding control operations. For example, icons can be displayed on the HMI, and the HMI can be used to operate these icons to perform specific functions, such as drawing a region of interest bounding box on the ultrasound image.

[0037] Optionally, the ultrasound imaging system 100 may also include other human-machine interface devices besides the display 118, which are connected to the processor 116. For example, the processor 116 may be connected to the human-machine interface device via an external input / output port, which may be a wireless communication module, a wired communication module, or a combination of both. The external input / output port may also be based on USB, bus protocols such as CAN, and / or wired network protocols.

[0038] The human-computer interaction device may include an input device for detecting user input information. This input information may be, for example, control commands for the timing of ultrasound transmission / reception, operational input commands for drawing points, lines, or boxes on an ultrasound image, or other types of commands. The input device may include one or a combination of several of the following: a keyboard, mouse, scroll wheel, trackball, mobile input device (e.g., a mobile device with a touchscreen, a mobile phone, etc.), a multi-function knob, etc. The human-computer interaction device may also include an output device such as a printer.

[0039] The ultrasound imaging system 100 may also include a memory 124 for storing instructions executed by the processor, stored received ultrasound echoes, stored ultrasound images, ultrasound contrast images, etc. The memory may be a flash memory card, solid-state memory, hard disk, etc. It may be volatile and / or non-volatile memory, removable memory and / or non-removable memory, etc.

[0040] It should be understood that Figure 1 The components included in the ultrasound imaging system 100 shown are merely illustrative and may include more or fewer components. This invention is not limited thereto.

[0041] The following reference Figure 2 The ultrasound contrast imaging method proposed in the embodiments of the present invention is described below. Figure 2 Figure 2A schematic flowchart of an ultrasound contrast imaging method 200 according to an embodiment of the present invention is shown. The ultrasound contrast imaging method 200 of this embodiment can be used in an ultrasound imaging system, which includes an ultrasound probe, a processor, and a display. This ultrasound imaging system can be implemented as the ultrasound imaging system 100 described above. Specifically, the ultrasound contrast imaging method 200 of this embodiment includes the following steps: In step S210, acquiring three-dimensional ultrasound data and three-dimensional contrast imaging data of a target tissue, wherein the target tissue contains a contrast agent; In step S220, acquiring the location information of artifact regions in the three-dimensional ultrasound data; In step S230, determining the location information of artifact regions in the three-dimensional contrast imaging data based on the location information of the artifact regions in the three-dimensional ultrasound data; In step S240, rendering the three-dimensional contrast imaging data to obtain a rendered image, and processing the artifact regions during the rendering process to weaken or remove the artifact regions in the rendered image. Alternatively, in another embodiment, in step S240, the data corresponding to the artifact region can be weakened or removed from the three-dimensional contrast imaging data, and the three-dimensional contrast imaging data after removing the data corresponding to the artifact region can be rendered to obtain a rendered image. The method of this application solves the aliasing interference on tissue structures caused by artifacts behind the contrast agent delivery tube in the contrast image, enabling the contrast image to clearly present the tissue structure at the artifact region, thereby effectively improving the diagnostic accuracy of doctors.

[0042] In step S210, the target tissue can be any tissue requiring ultrasound imaging. For example, the target tissue may include the fallopian tubes of the subject and tissues connected to the fallopian tubes, such as the uterine cavity and ovaries. Typically, during fallopian tube ultrasound imaging, contrast agent is injected into the uterine cavity and fallopian tubes through a contrast agent delivery tube. This process may involve first placing a balloon in the ovary, and then delivering the contrast agent through the contrast agent delivery tube. The balloon and contrast agent delivery tube have relatively low acoustic attenuation. Due to the posterior wall enhancement effect, artifacts appear behind the contrast agent delivery tube in the imaging. These artifacts overlap with the tissue structures and cannot be effectively distinguished, severely affecting the doctor's diagnostic process.

[0043] In the embodiments of this application, by controlling the ultrasound probe to emit ultrasound waves toward the target tissue containing the contrast agent, three-dimensional ultrasound data and three-dimensional contrast imaging data of the target tissue can be acquired simultaneously based on the echo of the ultrasound waves. Here, acquiring three-dimensional ultrasound data and three-dimensional contrast imaging data of the target tissue simultaneously does not necessarily mean acquiring the three-dimensional ultrasound data and three-dimensional contrast imaging data of the target tissue at the same time, but rather means that both three-dimensional ultrasound data and three-dimensional contrast imaging data can be acquired from the echo of the ultrasound waves.

[0044] It is worth noting that 3D ultrasound data refers to the three-dimensional data formed based on the ultrasound echoes of the target tissue during the contrast imaging process, while 3D contrast imaging data refers to the three-dimensional data formed by ultrasound imaging of the contrast agent during the contrast imaging process. Optionally, 3D ultrasound data can refer to B-mode data.

[0045] The acquisition of three-dimensional ultrasound data and three-dimensional contrast imaging data of the target tissue can be done in real time during ultrasound contrast imaging or by acquiring a frozen ultrasound film during ultrasound contrast imaging, which includes the three-dimensional ultrasound data and three-dimensional contrast imaging data of the target tissue.

[0046] In one example, in step S220, before performing subsequent artifact processing, it can be determined whether the artifact processing function is enabled. The artifact processing function refers to the function of weakening or removing artifacts. This function can be manually enabled by the user or enabled by default in the system (i.e., the ultrasound imaging system). When the artifact processing function is manually disabled by the user or by default in the system, volume rendering (VR) can be directly performed on the 3D contrast data acquired in step S210. Alternatively, even if the artifact processing function is enabled, volume rendering (VR) can still be performed on the 3D contrast data acquired in step S210 and displayed.

[0047] To facilitate users in enabling or disabling the artifact processing function, the human-computer interface of the ultrasound imaging system is equipped with function buttons for enabling or disabling the artifact processing function. Obtaining the activation command for the artifact processing function includes: obtaining the activation command input via the function button, for example, generating an activation command when an operation on the function button (e.g., via mouse click or touch) is detected, thereby enabling the artifact processing function; or, obtaining the activation command for the artifact processing function includes: when the artifact processing function in the ultrasound imaging system is enabled by default, directly obtaining the activation command from the ultrasound imaging system.

[0048] In step S220, the location information of the artifact regions in the three-dimensional ultrasound data can be obtained based on any suitable method. For example, artifact regions can be identified from the three-dimensional ultrasound data, and their location information can be obtained. Alternatively, for example, two-dimensional data of the artifact regions can be identified from multiple two-dimensional sections of the three-dimensional ultrasound data, and the location information of the artifact regions in the three-dimensional ultrasound data can be obtained based on the identified two-dimensional data of the artifact regions. Optionally, the multiple two-dimensional sections include at least a portion of the cross-sectional images used to construct the cross-sectional image of the three-dimensional ultrasound data, or the multiple two-dimensional sections include cross-sectional images extracted from the three-dimensional ultrasound data. For example, if the three-dimensional ultrasound data can be directly obtained by, for example, ultrasound volume probe scanning, then the cross-sectional images can be extracted from the three-dimensional ultrasound data.

[0049] In one example, a method for identifying artifact regions from 3D ultrasound data or 2D cross-sections of 3D ultrasound data could be to directly segment the artifact regions, for example, by directly segmenting the artifact regions from the 3D ultrasound data or 2D cross-sections of 3D ultrasound data. Segmentation can include traditional methods as well as machine learning methods.

[0050] Taking traditional methods as an example, artifact regions appear as obvious hyperechoic regions in three-dimensional ultrasound data such as B-mode ultrasound images. Traditional methods can segment artifact regions based on common features such as brightness, first-order gradient, and second-order gradient, as well as their combined features, and segment artifact regions through methods such as watershed, level set, region growing, and graph-cut.

[0051] For machine learning methods, a database needs to be constructed first. For 3D ultrasound data, a 3D ultrasound database is constructed; for 2D cross-sections of 3D ultrasound data, a 2D cross-section database is constructed. Each database contains at least one labeling result for artifacts in hysterosalpingography (HSG) ultrasound data. The machine learning method specifically employs an end-to-end semantic segmentation network based on deep learning. This network is constructed by stacking convolutional and fully connected layers. The final fully connected layer is removed, and upsampling or deconvolutional layers are added to make the input and output dimensions the same, thus directly obtaining the region of interest (ROI) and its corresponding category from the input data. Common networks include FCN, U-Net, and Mask R-CNN. Through this training, a pre-trained network model is obtained. Based on this model, artifact regions are segmented from 3D ultrasound data or 2D cross-sections of 3D ultrasound data.

[0052] In other examples, the above methods can be combined to identify artifact regions from three-dimensional ultrasound data or two-dimensional sections of three-dimensional ultrasound data.

[0053] In another example, a method for identifying artifact regions from three-dimensional ultrasound data or two-dimensional sections of three-dimensional ultrasound data may be to indirectly locate the artifact regions by identifying the delivery tube. For example, the position of the delivery tube may be identified and located from the three-dimensional ultrasound data or from multiple two-dimensional sections of the three-dimensional ultrasound data, wherein the delivery tube is used to deliver contrast agent to the target tissue; based on the position of the delivery tube, the positional information of the artifact regions in the three-dimensional ultrasound data may be obtained.

[0054] It is worth mentioning that, in this embodiment, the artifact region is the area located behind the delivery tube and defined by the ultrasonic waves emitted from the ultrasonic probe that cut through the outer wall of the delivery tube. The area behind the delivery tube is the side of the delivery tube facing away from the ultrasonic probe. Figure 3 As shown, by identifying the position of the fallopian tube contrast agent delivery tube (corresponding to...) Figure 3 The circular area), the area behind the fallopian tube contrast agent delivery tube (corresponding to...) Figure 3 The shadowed area is identified as the artifact area.

[0055] One method for identifying and locating the fallopian tube contrast agent delivery tube in an image from 3D ultrasound data or 2D cross-sections of 3D ultrasound data can be through machine learning. This machine learning approach also requires constructing a database of 3D ultrasound data or 2D cross-sections of 3D ultrasound data. The database contains at least one calibration result for the contrast agent delivery tube. The method for detecting the location of the contrast agent delivery tube can use any one or more of the following methods: For example, a sliding window-based method, including: first, extracting features from the region within the sliding window. Feature extraction methods can be traditional PCA, LDA, Haar features, texture features, etc., or deep neural networks can be used for feature extraction. Then, the extracted features are matched with the database, and discriminators such as KNN, SVM, random forest, and neural networks are used for classification to determine whether the current window contains the target category to be detected, i.e., whether the current window contains the delivery tube. This process involves traversing all regions of the 3D ultrasound data or 2D cross-sections of 3D ultrasound data to ultimately identify the delivery tube within the 3D ultrasound data or 2D cross-sections of 3D ultrasound data.

[0056] For example, a deep learning-based bounding-box detection method can identify and locate the position of the fallopian tube contrast agent delivery tube in an image from 3D ultrasound data or 2D cross-sections of 3D ultrasound data. This method may include the following steps: constructing a network by stacking base convolutional layers and fully connected layers, and learning features and regressing parameters on a volume database through the network. For an input volume dataset, the network can directly regress the bounding box of the corresponding target region, while simultaneously obtaining the category of the tissue structure within the target region. Common network architectures include R-CNN, FastR-CNN, Faster R-CNN, SSD, and YOLO.

[0057] For example, end-to-end semantic segmentation network methods based on deep learning can identify and locate the position of the fallopian tube contrast agent delivery tube in an image from 3D ultrasound data or 2D cross-sections of 3D ultrasound data. This type of method is structurally similar to the aforementioned deep learning-based Bounding-Box method. The difference is that the last fully connected layer of the network is removed, and an upsampling or deconvolution layer is added to make the input and output sizes the same, thereby directly obtaining the region of interest and its corresponding category of the input data. Common networks include FCN, U-Net, and Mask R-CNN.

[0058] Further, in step S230, based on the location information of the artifact regions in the three-dimensional ultrasound data, the location information of the artifact regions in the three-dimensional contrast imaging data is determined.

[0059] In 3D contrast imaging data, each line is formed by combining the echoes from three ultrasound waves emitted at different voltages. The 3D ultrasound data represents the echo from one of these emitted waves. For example, if the three emission voltages are 0.5V, 1V, and 0.5V, and the acquired echo data are R1, R2, and R3 respectively, then the formula for calculating the contrast imaging data R4 is:

[0060] R4 = R1 + R3 - R2

[0061] R2 represents the 3D ultrasound data. The above example illustrates the general process of obtaining 3D contrast imaging data and 3D ultrasound data; the actual process may be adjusted based on different voltages. Therefore, the size and spatial position of the images in 3D ultrasound data and 3D contrast imaging data correspond, and the artifact regions in the 3D ultrasound data are the same as the artifact regions in the 3D contrast imaging data. The posterior wall enhancement effect during ultrasound imaging can lead to excessive brightness compensation behind the contrast agent delivery tube, appearing as a bright artifact region in the 3D ultrasound data obtained during fallopian tube contrast imaging or in the 2D section of the 3D ultrasound data. These artifact regions are relatively easy to distinguish. Therefore, artifact regions in ultrasound images can be identified through 3D ultrasound data. Since the size and spatial position of the images in 3D ultrasound data and 3D contrast imaging data correspond, the artifact regions in 3D ultrasound data are the same as the artifact regions in the 3D contrast imaging data.

[0062] Further, in step S240, the three-dimensional imaging data is rendered to obtain a rendered image. During the rendering process, the artifact regions are processed to weaken or remove the artifact regions in the rendered image. Alternatively, the data corresponding to the artifact regions in the three-dimensional imaging data is weakened or removed from the three-dimensional imaging data, and the three-dimensional imaging data after removing the data corresponding to the artifact regions is rendered to obtain the rendered image. Any suitable method can be used to weaken or remove the artifact regions in the rendered image or the data corresponding to the artifact regions in the three-dimensional imaging data.

[0063] Furthermore, in the embodiments of this application, the three-dimensional imaging data (which may be the original three-dimensional imaging data or the processed three-dimensional imaging data, such as the data after removing the imaging data corresponding to the artifact region as described above) may be rendered using any suitable method known to those skilled in the art, for example, volume rendering.

[0064] Volume rendering primarily utilizes ray tracing algorithms and can include the following modes: Surface rendering mode displaying object surface information; Max echo mode displaying maximum internal echo information; Min echo mode displaying minimum internal echo information; X-ray mode displaying internal structural information; Volume Rendering with Global Illumination mode displaying object surface information; Silhouette mode displaying object's internal and external contour information through a semi-transparent effect; and Temporal pseudo-color rendering mode highlighting newly added imaging or tissue data on the object's surface at different times (with different pseudo-colors assigned to newly added imaging or tissue data over time). The appropriate volume rendering mode can be selected based on specific needs and / or user settings.

[0065] Taking the rendering of the 3D imaging data using a ray tracing algorithm to obtain a rendered image as an example, the process includes: emitting multiple rays through the volume data based on the viewing direction; each ray advancing at a fixed step size; sampling the volume data along the ray path; calculating the color and opacity of each sampling point; accumulating the color and opacity along each ray path (for example, mapping the opacity of each sampling point to a color value according to an opacity-color mapping table, and then accumulating the color values ​​of each sampling point along each ray path to obtain an accumulated color value); and finally mapping the accumulated color value onto each pixel of the 2D image to obtain the VR rendered image. Through VR rendering, 3D data is transformed into 2D data, thus the VR rendered image can be displayed on a screen.

[0066] The above rendering process also applies to the rendering of three-dimensional ultrasound data, and will not be described again here.

[0067] Artifact reduction refers to the weakening of the display effect of artifact areas in the final VR rendering image of an ultrasound imaging system, such as lighter colors or higher transparency. In one example, the processing includes a reduction process, which is performed on the artifact areas during the rendering process. This includes increasing the transparency of the artifact areas to a target transparency level, for example, increasing the transparency of the sampling points of the artifact areas to the target transparency level. This can be achieved by adding transparency to the artifact areas during volume rendering (VR) of the 3D imaging data. Optionally, the data transparency can be mapped by looking up a mapping table. At this point, the internal tissue structures obscured by the artifacts can be seen through the artifact areas. The target transparency can be set in any suitable way. For example, the target transparency can be a preset value in the ultrasound imaging system. Alternatively, if a first control is provided in the human-computer interaction interface of the ultrasound imaging system to adjust the transparency of the artifact area, the target transparency can also be determined by the ultrasound imaging system based on the input information entered through the first control. The first control can be any suitable control known to those skilled in the art. For example, the first control can correspond to multiple options for target transparency. The ultrasound imaging system can detect operations on the options in the first control and adjust the target transparency to the transparency corresponding to the selected option. Alternatively, the first control can also include a slider and a slider. The ultrasound imaging system can detect operations on the slider in the first control and adjust the target transparency to the transparency corresponding to the transparency indicated by the slider.

[0068] In another example, the processing includes a weakening process performed on the artifact region during the rendering process. This weakening includes: reducing the pixel values ​​of the artifact region to a target pixel value during the rendering process, or reducing the pixel values ​​of the artifact region by a target ratio during the rendering process, for example, adjusting the pixel values ​​of the sampling points corresponding to the artifact region. By adjusting the pixel values ​​of the artifact region, the artifact region can be made to darken or become transparent, thereby allowing the area it covers to be revealed.

[0069] The target pixel value or target ratio is a preset value in the ultrasound imaging system. The target pixel value or target ratio is determined by the ultrasound imaging system based on input information input through a second control. This second control is located in the human-computer interaction interface of the ultrasound imaging system. For example, the user can manually adjust the pixel value or the ratio using this control. Optionally, the type of the second control can be any suitable type known to those skilled in the art. For example, it can consist of a slider and a slider on the slider, with the slider's position corresponding to the position of the pixel value to be adjusted. Alternatively, it can be an input field used to receive the specific numerical value of the input pixel value, etc.

[0070] In one example, the processing includes a weakening process performed on the artifact region during the rendering process. This weakening includes adjusting the color of the artifact region during the rendering process, for example, adjusting the color of the sampling point corresponding to the artifact region to differentiate the display of the artifact region and the area covered by the artifact region. For example, the artifact region and the area covered by the artifact region can be displayed using different colors. For instance, the artifact region can be displayed using a lighter color, while the area covered by the artifact region can be displayed using a darker color, thereby visually distinguishing the two by the user. Optionally, the type of the third control can be any suitable type well known to those skilled in the art. For example, the third control includes multiple color options, and when any option is selected, the color of the artifact region is adjusted to the corresponding color.

[0071] For example, the color of the artifact region is a preset color of the ultrasound imaging system, or the color of the artifact region is determined by the ultrasound imaging system based on input information from a third control provided by the user, which is set in the human-computer interaction interface of the ultrasound imaging system.

[0072] In addition to the methods described above for weakening artifact regions, artifact regions can also be removed. Artifact removal refers to eliminating the structure corresponding to the artifact region in the final VR rendering image of the system. For example, the artifact removal process during rendering includes: setting the voxel value corresponding to the artifact region in the 3D imaging data to a target voxel value, and then rendering the 3D imaging data to obtain a rendering image. When the voxel value is the target voxel value, the artifact region will not be displayed in the rendering image. The target voxel value can be a very small value in the 3D imaging data, such as 0. In this way, the artifact region will not be displayed in the VR rendering image, thus allowing the area it covers to be displayed.

[0073] The methods described above for processing artifact regions can be used individually or in combination.

[0074] In another example, artifact removal can also be performed during the rendering process. For instance, multiple rays are emitted based on the viewing direction, passing through the 3D image data. Each ray advances according to a preset step size, sampling the 3D image data along each ray path. The color and transparency of each sampling point are calculated, where each sampling point includes at least one first sampling point located in the artifact region and multiple second sampling points not located in the artifact region. The color and transparency of the second sampling points along each ray path are accumulated to perform the artifact removal process. The accumulated color values ​​are mapped to each pixel of the 2D image to obtain the rendered image. Since the location information of the artifact region has been obtained in the aforementioned steps, when the location of a sampling point is within the artifact region, it can be determined that the sampling point corresponds to the first sampling point, and thus the first sampling point is not rendered, thereby achieving artifact removal.

[0075] Optionally, the different brightness of each sampling point can be determined based on the grayscale value of each sampling point. For example, accumulating the color and transparency of the second sampling points along each light path includes: mapping the opacity of each second sampling point to a color value according to an opacity-color mapping table, and then accumulating the color values ​​of each second sampling point along each light path to obtain a cumulative color value. Alternatively, accumulating the color and transparency of the second sampling points along each light path includes: accumulating the opacity of each second sampling point along each light path to obtain a cumulative opacity, and finally mapping the cumulative opacity along each light path to a cumulative color value using a cumulative opacity-color mapping table.

[0076] In one example, the method of this application further includes: displaying the obtained rendering image so that the user can diagnose the subject based on the rendering image. For example, it is convenient for the user to diagnose whether the fallopian tubes of the subject are open based on the rendering image (also called the hysterosalpingography image) obtained by rendering the three-dimensional hysterosalpingography data during the fallopian tube imaging process. Furthermore, since the method of this application can weaken or remove artifacts, the tissue structure area corresponding to the artifact area in the presented rendering image is clearer.

[0077] In another example, the method of this application includes displaying a rendered image and a rendered image obtained after rendering 3D angiographic data without weakening or removing the artifact regions, such as... Figure 4 As shown, the left image is a VR rendering of the original 3D angiography data, and the right image is a VR rendering of the angiography after artifact removal. The raised structure within the white box in the left image represents the artifact area, while the white box in the right image shows the result after artifact removal, allowing users to compare and observe.

[0078] In other examples, the method of this application also includes displaying an image rendered from three-dimensional ultrasound data.

[0079] This concludes the description of the main steps of the ultrasound contrast imaging method of this application. However, it is worth mentioning that the complete ultrasound contrast imaging method may include other steps, or, without contradiction, the aforementioned steps may be interspersed or their order may be changed.

[0080] In summary, the method of this application locates the artifact region using three-dimensional ultrasound data and processes the artifact region during the rendering of the three-dimensional contrast imaging data to weaken or remove the artifact region in the rendered image. This solves the problem of aliasing interference on tissue structures caused by artifacts behind the contrast agent delivery tube in the contrast imaging image, which makes it impossible to distinguish between artifacts and normal tissue structures when observing the contrast imaging image. This allows the contrast imaging image to clearly present the tissue structure at the artifact region, thereby effectively improving the diagnostic accuracy of doctors.

[0081] This invention also provides an ultrasound imaging system for implementing the aforementioned ultrasound contrast imaging method 200. The ultrasound imaging system includes an ultrasound probe, a transmitting circuit, a receiving circuit, a processor, and a display. (Refer to previous text) Figure 1 This ultrasound imaging system can achieve the following: Figure 1The ultrasound imaging system 100 shown 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 system 100 may also include a transmit / receive selection switch 120 and a beamforming module 122. The transmitting circuit 112 and the receiving circuit 114 can be connected to the ultrasound probe 110 via the transmit / receive selection switch 120. The relevant descriptions of each component can be found in the preceding descriptions and will not be repeated here. The ultrasound probe 110 may be a volumetric ultrasound probe or an area array ultrasound probe, etc.

[0082] The transmitting circuit 112 controls the ultrasound probe 110 to emit ultrasound waves toward the target tissue containing the contrast agent; the receiving circuit 114 receives the ultrasound echo and obtains the ultrasound echo signal; the processor 116 acquires three-dimensional ultrasound data and three-dimensional contrast imaging data of the target tissue based on the ultrasound echo signal; the processor 116 is also used to execute the ultrasound contrast imaging method 200 or ultrasound contrast imaging method 1000 described above; when the processor 116 executes the ultrasound contrast imaging method 200 or ultrasound contrast imaging method 1000, the display 118 displays arbitrary visualization information, such as a rendered image, etc.

[0083] The above only describes the main functions of each component of the ultrasound imaging system. For more details, please refer to the relevant description in Ultrasound Contrast Imaging Method 200, which will not be repeated here.

[0084] The ultrasound imaging system of this invention can locate artifact regions through three-dimensional ultrasound data and process the artifact regions during the rendering of three-dimensional contrast imaging data to weaken or remove the artifact regions in the rendered image. This solves the problem of aliasing interference on tissue structures caused by artifacts behind the contrast agent delivery tube in the contrast image, allowing the contrast image to clearly present the tissue structure at the artifact region, thereby effectively improving the diagnostic accuracy of doctors.

[0085] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of the invention. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of the invention. All such changes and modifications are intended to be included within the scope of the invention as claimed in the appended claims.

[0086] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0087] In the several embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0088] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0089] Similarly, it should be understood that, in order to streamline the invention and aid in understanding one or more of the various aspects of the invention, features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of the invention. However, this approach should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with fewer features than all of those in a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0090] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0091] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0092] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules according to embodiments of the present invention. The present invention can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing some or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0093] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0094] The above description is merely a specific embodiment of the present invention or an explanation of that embodiment. The scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An ultrasonic contrast imaging method, characterized by, The method includes: Acquire three-dimensional ultrasound data and three-dimensional contrast imaging data of a target tissue, wherein the target tissue contains a contrast agent; The location information of the artifact region in the three-dimensional ultrasound data is obtained. The artifact region is located behind the delivery tube and is defined by the ultrasound waves emitted from the ultrasound probe that cut through the outer wall of the delivery tube. The delivery tube is used to deliver contrast agent to the target tissue. The area behind the delivery tube is the side of the delivery tube that is away from the ultrasound probe. Based on the location information of the artifact regions in the three-dimensional ultrasound data, the location information of the artifact regions in the three-dimensional contrast imaging data is determined; The three-dimensional imaging data is rendered to obtain a rendered image, and the artifact regions are processed during the rendering process to weaken or remove the artifact regions in the rendered image; or, the data corresponding to the artifact regions is weakened or removed from the three-dimensional imaging data, and the three-dimensional imaging data after removing the data corresponding to the artifact regions is rendered to obtain a rendered image.

2. The imaging method of claim 1, wherein, The step of obtaining the location information of the artifact region in the three-dimensional ultrasound data includes: Obtain the command to enable the artifact processing function; In response to the activation command, the location information of the artifact region in the three-dimensional ultrasound data is obtained.

3. The imaging method of claim 2, wherein, The imaging method is applied to an ultrasound imaging system. The human-computer interface of the ultrasound imaging system is provided with function buttons for turning the artifact processing function on or off. Obtaining the activation command of the artifact processing function includes: obtaining the activation command input through the function buttons. or, When the artifact processing function in the ultrasound imaging system is enabled by default, the activation command is obtained directly from the ultrasound imaging system.

4. The imaging method as described in claim 1, characterized in that, The step of obtaining the location information of the artifact region in the three-dimensional ultrasound data includes: Identify artifact regions from the three-dimensional ultrasound data and obtain the location information of the artifact regions in the three-dimensional ultrasound data, or... Two-dimensional data of artifact regions are identified from multiple two-dimensional sections of the three-dimensional ultrasound data, and the location information of the artifact regions in the three-dimensional ultrasound data is obtained based on the identified two-dimensional data of the artifact regions.

5. The imaging method as described in claim 1, characterized in that, The step of obtaining the location information of the artifact region in the three-dimensional ultrasound data includes: The position of the delivery tube is identified and located from the three-dimensional ultrasound data or from multiple two-dimensional sections of the three-dimensional ultrasound data; Based on the position of the delivery tube, the location information of the artifact region in the three-dimensional ultrasound data is obtained.

6. The imaging method as described in claim 4 or 5, characterized in that, The plurality of two-dimensional sections include at least a portion of the section images used to construct the section images of the three-dimensional ultrasound data, or the plurality of two-dimensional sections include section images extracted from the three-dimensional ultrasound data.

7. The imaging method as described in claim 1, characterized in that, The processing includes a weakening process, which is performed on the artifact regions during the rendering process, including: During the rendering process, the transparency of the artifact region is increased to the target transparency.

8. The imaging method as described in claim 7, characterized in that, The target transparency is a preset value in the ultrasound imaging system, or The target transparency is determined by the ultrasound imaging system based on input information entered through a first control, wherein the first control is set in the human-computer interaction interface of the ultrasound imaging system.

9. The imaging method as described in claim 1, characterized in that, The processing includes a weakening process, which is performed on the artifact regions during the rendering process, including: During the rendering process, the pixel values ​​of the artifact region are reduced to the target pixel values, or the pixel values ​​of the artifact region are reduced according to the target ratio during the rendering process.

10. The imaging method as described in claim 9, characterized in that, The target pixel value or the target ratio is a preset value in the ultrasound imaging system, or The target pixel value or the target ratio is determined by the ultrasound imaging system based on input information input through a second control, which is set in the human-computer interaction interface of the ultrasound imaging system.

11. The imaging method as described in claim 1, characterized in that, The processing includes a weakening process, which is performed on the artifact regions during the rendering process, including: During the rendering process, the color of the artifact region is adjusted to differentiate the display of the artifact region and the area covered by the artifact region.

12. The imaging method as described in claim 11, characterized in that, The color of the artifact region is a preset color of the ultrasound imaging system, or The color of the artifact region is determined by the ultrasound imaging system based on the input information provided by the user's third control, which is set in the human-computer interaction interface of the ultrasound imaging system.

13. The imaging method as described in claim 1, characterized in that, The processing includes a removal process, which is performed on the artifact regions during the rendering process, including: The voxel value corresponding to the artifact region in the three-dimensional imaging data is set as the target voxel value, and then the three-dimensional imaging data is rendered to obtain a rendering image. When the voxel value is the target voxel value, the artifact region will not be displayed in the rendering image.

14. The imaging method as described in claim 13, characterized in that, The target voxel value is 0.

15. The imaging method as described in claim 1, characterized in that, The processing includes removal processing, wherein rendering the 3D imaging data to obtain a rendered image, and removing artifact regions during the rendering process, includes: Multiple rays are emitted based on the line of sight, passing through the three-dimensional imaging data; Each ray advances according to a preset step size, and the three-dimensional imaging data on each ray path is sampled; Calculate the color and transparency of each sampling point, wherein each sampling point includes at least one first sampling point located in the artifact region and multiple second sampling points not located in the artifact region; The color and transparency of the second sampling point on each light path are accumulated to perform the artifact removal process on the artifact region; Accumulated color values ​​are mapped onto each pixel of a two-dimensional image to obtain a rendered image.

16. The imaging method as described in claim 1, characterized in that, The imaging method further includes: Display the rendered image; or The rendered image is shown, as well as the rendered image obtained after rendering the 3D animation data without weakening or removing the artifact regions.

17. The imaging method according to any one of claims 1 to 16, characterized in that, The target tissue includes the fallopian tubes.

18. An ultrasound imaging system, characterized in that, The ultrasound imaging system includes: Ultrasonic probe; A transmitting circuit is used to control the ultrasound probe to emit ultrasound waves toward the target tissue containing the contrast agent; A receiving circuit is used to receive the ultrasonic echo of the ultrasonic wave and obtain an ultrasonic echo signal; The processor is used to acquire three-dimensional ultrasound data and three-dimensional contrast data of the target tissue based on the ultrasound echo signal; Memory is used to store executable program instructions; The processor is further configured to execute the program instructions stored in the memory, causing the processor to perform the ultrasound contrast imaging method as described in any one of claims 1 to 17; A monitor is used to display visual information.

Images