A method and system for monitoring backflow

Abstract

This application discloses a method and system for monitoring backflow. The monitoring method includes: acquiring color Doppler data of a target area; determining backflow information for each frame of a multi-frame color Doppler image based on the color Doppler data; and generating a backflow information data map based on the backflow information of each frame of the color Doppler image, wherein the backflow information data map reflects the correspondence between the frame number of the multi-frame color Doppler images and the backflow information in each frame of the color Doppler image.

Description

Technical Field

[0001] This specification relates to the field of medical technology, and in particular to a method and system for monitoring reflux. Background Technology

[0002] Visual observation of valvular regurgitation is currently the most widely used diagnostic method. However, it is a qualitative diagnostic tool, and its quantitative value is greatly affected by factors such as operator subjectivity, measurement speed, intracardiac pressure, and volume. Furthermore, it can easily lead to missed diagnoses by inexperienced physicians or for pathological regurgitation with small regurgitation volumes.

[0003] Therefore, there is an urgent need for a real-time, automatic, and effective method for monitoring valvular regurgitation. Summary of the Invention

[0004] One embodiment of this specification provides a method for monitoring backflow. The monitoring method includes: acquiring color Doppler data of a target area; determining backflow information of each frame of a multi-frame color Doppler image based on the color Doppler data; and generating a backflow information data map based on the backflow information of each frame of the color Doppler image, wherein the backflow information data map reflects the correspondence between the frame number of the multi-frame color Doppler images and the backflow information in each frame of the color Doppler image.

[0005] One embodiment of this specification provides a backflow monitoring system. The monitoring system includes: an acquisition module for acquiring color Doppler data of a target area; a determination module for determining backflow information of each frame of a multi-frame color Doppler image based on the color Doppler data; and a generation module for generating a backflow information data map based on the backflow information of each frame of the color Doppler image, wherein the backflow information data map reflects the correspondence between the frame number of the multi-frame color Doppler images and the backflow information in each frame of the color Doppler image.

[0006] One embodiment of this specification provides a backflow monitoring device, including a processor for executing the backflow monitoring method.

[0007] One embodiment of this specification provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions from the storage medium, the computer executes the backflow monitoring method.

[0008] Some embodiments of this application use color Doppler data to calculate the reflux ROI in an image frame, track blood flow by updating the position of detected blood flow in the ROI region, and calculate reflux area data to achieve quantitative analysis. Attached Figure Description

[0009] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0010] Figure 1 This is a schematic diagram illustrating an application scenario of an exemplary backflow monitoring system according to some embodiments of this specification;

[0011] Figure 2 This is a block diagram of an exemplary backflow monitoring system according to some embodiments of this specification;

[0012] Figure 3 This is an exemplary flowchart of a backflow monitoring method according to some embodiments of this specification;

[0013] Figure 4 This is a schematic diagram of mitral regurgitation according to other embodiments of this specification;

[0014] Figure 5 These are schematic diagrams of exemplary ultrasound imaging operation interfaces shown in some embodiments of this specification;

[0015] Figure 6 This is a schematic diagram of an exemplary ultrasound imaging operation interface shown according to some embodiments of this specification. Detailed Implementation

[0016] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0017] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0018] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0019] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0020] Figure 1 This is a schematic diagram of an exemplary backflow monitoring system according to some embodiments of this specification.

[0021] like Figure 1 As shown, the application scenario 100 of the backflow monitoring system may include an ultrasonic testing device 110, a processing device 120, a terminal device 130, a storage device 140, and a network 150.

[0022] Ultrasonic testing equipment 110 refers to a device that acquires images / videos of an object by utilizing the propagation laws of ultrasound in a medium, such as ultrasound pulse echo imaging equipment, ultrasound echo Doppler imaging equipment, ultrasound electronic endoscope, ultrasound Doppler blood flow analysis equipment, and ultrasound human tissue measurement equipment. The object is the subject of the examination, such as a patient or injured person. In some embodiments, the object can be examined in any position, such as supine, lateral, prone, semi-recumbent, or sitting. In some embodiments, the scanning methods of ultrasonic testing equipment 110 may include A-mode ultrasound (Amplitude Modulated Ultrasound), B-mode ultrasound (Brightness Modulated Ultrasound), M-mode ultrasound (Motion Ultrasound), and D-mode ultrasound (Doppler Ultrasound). In some embodiments, ultrasonic testing equipment 110 can be installed in medical facilities or locations, such as wards, delivery rooms, examination rooms, operating rooms, emergency rooms, and ambulances. In some embodiments, ultrasonic testing equipment 110 can transmit ultrasound data to processing equipment 120 via network 150. The above description of the ultrasonic testing equipment 110 is for illustrative purposes only and is not intended to limit the scope of this specification.

[0023] The processing device 120 can process data and / or information acquired from the ultrasonic testing device 110, the terminal device 130, the storage device 140, and / or other components of the backflow monitoring system in the application scenario 100. For example, the processing device 120 can acquire ultrasonic data from the ultrasonic testing device 110, the terminal device 130, and the storage device 140, and analyze and process it.

[0024] In some embodiments, the processing device 120 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, the processing device 120 may be local or remote. For example, the processing device 120 may access information and / or data from the ultrasound testing device 110, the terminal device 130, and / or the storage device 140 via a network 150. Alternatively, the processing device 120 may be directly connected to the ultrasound testing device 110, the terminal device 130, and / or the storage device 140 to access information and / or data. In some embodiments, the processing device 120 may be implemented on a cloud platform. For example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud cloud, a multi-cloud, or any combination thereof.

[0025] In some embodiments, the processing device 120 and the ultrasonic testing device 110 may be integrated into one unit. In some embodiments, the processing device 120 and the ultrasonic testing device 110 may be directly or indirectly connected to work together to implement the methods and / or functions described herein.

[0026] In some embodiments, the processing device 120 may include input devices and / or output devices. The input devices and / or output devices enable interaction with the user (e.g., interaction with a backflow information data graph, etc.). In some embodiments, the input devices and / or output devices may include a display screen, keyboard, mouse, microphone, trackball, etc., or any combination thereof.

[0027] Terminal device 130 can communicate and / or connect to ultrasonic testing device 110, processing device 120, and / or storage device 140. In some embodiments, interaction with a user can be achieved through terminal device 130. In some embodiments, terminal device 130 may include mobile device 131, tablet computer 132, laptop computer 133, etc., or any combination thereof. In some embodiments, terminal device 130 (or all or part of its functions) may be integrated into processing device 120.

[0028] Storage device 140 may store data, instructions, and / or any other information. In some embodiments, storage device 140 may store data (e.g., ultrasound data, backflow information, etc.) acquired from ultrasound detection device 110, processing device 120, and / or terminal device 130. In some embodiments, storage device 140 may store data and / or instructions used by processing device 120 to perform or use in order to complete the exemplary methods described herein.

[0029] In some embodiments, storage device 140 may include one or more storage components, each of which may be a separate device or part of another device. In some embodiments, storage device 140 may include random access memory (RAM), read-only memory (ROM), mass storage, removable memory, volatile read-write memory, and any combination thereof. In some embodiments, storage device 140 may be implemented on a cloud platform. In some embodiments, storage device 140 may be part of ultrasonic detection device 110, processing device 120, and / or terminal device 130.

[0030] Network 150 may include any suitable network capable of facilitating information and / or data exchange. In some embodiments, at least one component of application scenario 100 of the backflow monitoring system (e.g., ultrasound detection device 110, processing device 120, terminal device 130, storage device 140) may exchange information and / or data with at least one other component of application scenario 100 of the backflow monitoring system via network 150. For example, processing device 120 may acquire ultrasound data from ultrasound detection device 110 via network 150.

[0031] It should be noted that the above description of the application scenario 100 of the reflux monitoring system is provided for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can make various modifications or variations based on the description in this specification. For example, the application scenario 100 of the reflux monitoring system can achieve similar or different functions on other devices. However, these changes and modifications will not depart from the scope of this specification.

[0032] Figure 2 This is a block diagram of an exemplary backflow monitoring system according to some embodiments of this specification.

[0033] like Figure 2 As shown, in some embodiments, the scanning system 200 may include an acquisition module 210, a determination module 220, and a generation module 230.

[0034] The acquisition module can be used to acquire color Doppler data of the target area. For more information on acquiring color Doppler data of the target area, please refer to step 310 and its related description.

[0035] The determination module can be used to determine the backflow information of each frame of a multi-frame color Doppler image based on color Doppler data. More information on determining the backflow information can be found in step 320 and its related description.

[0036] The generation module is used to generate a backflow information data map based on the backflow information of each frame of color Doppler image. The backflow information data map reflects the correspondence between the frame number of multiple color Doppler images and the backflow information in each frame of color Doppler image. For more information on the generation of the backflow information data map, please refer to step 330 and its related description.

[0037] It should be understood that Figure 2 The systems and modules shown can be implemented in various ways. For example, they can be implemented by hardware, software, or a combination of both. The systems and modules in this specification can be implemented not only by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips and transistors, or programmable hardware devices such as field-programmable gate arrays and programmable logic devices, but also by software, for example, executed by various types of processors, or by a combination of the aforementioned hardware circuits and software (e.g., firmware).

[0038] It should be noted that the above description of the system and its modules is for illustrative purposes only and should not be construed as limiting this specification to the scope of the illustrated embodiments. It is understood that those skilled in the art, after understanding the principles of this system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from these principles.

[0039] Figure 3 This is an exemplary flowchart of a backflow monitoring method according to some embodiments of this specification.

[0040] Step 310: Acquire color Doppler data of the target area. In some embodiments, step 310 may be performed by the processing device 120 or the acquisition module 210.

[0041] The target site refers to the area being detected. In some embodiments, the target site may include a specific part of the body, such as the heart. In some embodiments, the target site may include a specific organ, such as the heart.

[0042] In some embodiments, the target site includes one of the following: the tricuspid valve, the mitral valve, or the aortic valve.

[0043] Color Doppler (also known as two-dimensional Doppler) data refers to data obtained by processing echo information using the Doppler principle. In some embodiments, color Doppler data can be displayed as a real-time color spectrogram. In some embodiments, color Doppler data may include color Doppler image data, blood flow information, etc. Blood flow information may include phase information of blood flow, spectral information of blood flow, spatial information of blood flow, and image information of blood flow (e.g., color grayscale encoding information), etc.

[0044] In some embodiments, the acquisition module 210 can acquire color Doppler data of the target area in real time from the ultrasonic testing device 110. In some embodiments, the acquisition module 210 can acquire color Doppler data of the target area from the storage device 140, the storage unit of the processing device 120, etc. In some embodiments, the acquisition module 210 can acquire color Doppler data of the target area by reading from the storage device, the database, calling the data interface, etc.

[0045] Step 320: Based on the color Doppler data, determine the backflow information of each frame of the color Doppler image in the multi-frame color Doppler images. In some embodiments, step 320 may be performed by the processing device 120 or the determining module 220.

[0046] In some embodiments, a multi-frame color Doppler image may include all image frames from the color Doppler imaging process. In some embodiments, a multi-frame color Doppler image may consist only of image frames exhibiting reflux. Image frames exhibiting reflux can be obtained by filtering all image frames. For example, all image frames can be filtered based on the area of ​​the reflux region, and image frames whose reflux region area reaches a certain threshold can be selected as multi-frame color Doppler images.

[0047] Reflux information refers to information reflecting the blood reflux situation at a target site. For example, reflux information may include whether reflux occurs, the location of reflux, and the amount of refluxed blood flow.

[0048] In some embodiments, the regurgitation information includes at least one of the following: the length of the regurgitation region, the width of the regurgitation region, the area of ​​the regurgitation region, the direction of blood flow in the regurgitation region, or the velocity of blood flow in the regurgitation region. In some embodiments, the direction of blood flow in the regurgitation region (also referred to as the regurgitation direction) can refer to the reverse of the normal blood flow direction at the target site. Taking the tricuspid valve as the target site as an example, under normal circumstances, blood flows from the right atrium through the tricuspid valve into the right ventricle, so the normal blood flow direction is from the right atrium to the right ventricle. At this time, the direction of blood flow in the regurgitation region can be from the right ventricle to the right atrium. In some embodiments, the length of the regurgitation region refers to the maximum distance of the edge of the regurgitation region along the regurgitation direction. The width of the regurgitation region refers to the maximum distance of the edge of the regurgitation region along a direction perpendicular to the regurgitation direction. The area of ​​the regurgitation region refers to the area occupied by the regurgitation region in the image frame. The velocity of blood flow in the regurgitation region can refer to the distance the blood flow in the regurgitation region moves per unit time along the regurgitation direction.

[0049] In some embodiments, the determining module 220 can determine the reflux information of each frame of a multi-frame color Doppler image using various methods. For example, the reflux information of the multi-frame color Doppler images can be determined by image processing. For instance, the determining module 220 can segment the reflux region of each frame of the color Doppler image using image segmentation methods such as threshold segmentation, edge detection segmentation, region segmentation, clustering segmentation, graph theory segmentation, variational equation segmentation, and neural network segmentation. Further image calculations are performed based on the segmented reflux regions to determine the length, width, and area of ​​the reflux regions. In some embodiments, conventional blood flow locations (pixels) in the color Doppler image are displayed in blue, while locations where reflux occurs are displayed in red. The determining module 220 can define the red areas as reflux regions and further determine the length, width, and area of ​​the reflux regions based on ultrasound measurements.

[0050] In some embodiments, the determining module 220 can determine the reflux information based on the RGB values ​​of pixels in the color Doppler image data. For example, the determining module 220 can identify pixels in the color Doppler image data whose RGB values ​​are within the red threshold range, delineate reflux regions based on these pixels, and then calculate the length, width, and area of ​​the reflux regions based on the number of pixels in the reflux regions.

[0051] In some embodiments, the determining module 220 can perform blood flow imaging of the target site based on the Doppler effect (different ultrasound signals can be detected for blood flow in different directions).

[0052] In some embodiments, the determining module 220 may determine the blood flow velocity in the reflux region based on the Doppler frequency shift. The Doppler frequency shift is the difference between the receiving frequency at the receiver and the transmitting frequency at the transmitter. For example, the determining module 220 may determine the blood flow velocity in the reflux region based on the following formula (1).

[0053]

[0054] In this equation, the Doppler frequency shift Δf can be obtained by f"-f, where f is the frequency of the ultrasonic wave emitted by the transmitter, and f" is the frequency of the scattered echo received by the receiver, which can be calculated; c is the speed of ultrasonic wave propagation in blood, approximately 1570 m / s; v is the velocity of red blood cells, and the component of the red blood cell velocity in the direction of ultrasonic wave incidence is vcosθ; θ is the angle between the incident and scattered ultrasonic waves and the direction of blood flow. To obtain the maximum frequency shift signal, the ultrasonic beam should be at a fixed angle with the direction of blood flow, for example, θ equals 50°. Thus, only v is an unknown quantity in the above formula (1), and the blood flow velocity in the reflux region can be obtained based on formula (1).

[0055] In some embodiments, if v in formula (1) is negative, it means that the blood flows away from the direction of the probe and the corresponding frequency shift Δf is negative. Therefore, the determination module 220 can also determine the direction of blood flow based on the sign of Δf.

[0056] Compared to observing color Doppler images with the naked eye, identifying pixels in the color Doppler image data whose RGB values ​​are within the red threshold range can capture even smaller backflow signals that are invisible to the naked eye, making backflow monitoring more accurate.

[0057] In some embodiments, the determining module 220 can determine the degree of reflux at the target site based on the reflux information data map. In some embodiments, the degree of reflux can be a numerical value or index reflecting the severity of reflux in the blood flow at the target site. For example, the degree of reflux can include severe reflux, moderate reflux, mild reflux, etc. A description of the degree of reflux can be found in this specification. Figure 4 And related descriptions. In some embodiments, when the multi-frame color Doppler images are all color Doppler images acquired during ultrasound imaging, the determining module 220 can determine the longest length of the reflux region of the target site in the multi-frame color Doppler images as a parameter for determining the degree of reflux in the target site based on the reflux information of each frame of the images. In some embodiments, when the multi-frame color Doppler images are all color Doppler images acquired during ultrasound imaging, the determining module 220 can determine the length of the reflux region of the target site in each frame of the multi-frame color Doppler images based on the reflux information of each frame of the images, and determine the degree of reflux in the target site in each frame based on the length of the reflux region of the target site in each frame. In some embodiments, when the multi-frame color Doppler images are selected image frames with blood flow reflux, the determining module 220 can determine the degree of reflux in the target site based on the reflux information of each frame of the images. For example, the determining module 220 can process the length of the reflux region in each frame of a multi-frame color Doppler image with reflux (e.g., average value calculation, weighted average value calculation, etc.), and determine the degree of reflux at the target location based on the length of the processed reflux region.

[0058] In some embodiments, the determining module 220 can issue a reflux warning signal based on the degree of reflux at the target site. The reflux warning signal can be a prompt reflecting the degree of blood reflux at the target site. In some embodiments, the determining module 220 can issue a reflux warning signal based on the degree of reflux at the target site after ultrasound imaging. In some embodiments, the determining module 220 can issue a reflux warning signal in real time for each frame of color Doppler image after each frame of color Doppler image is acquired, based on the degree of reflux at the target site in that frame.

[0059] In some embodiments, the determining module 220 can determine the length of the reflux region of the target site based on the reflux information of each frame of color Doppler images in multiple frames of color Doppler images. For example, the determining module 220 can identify pixels in the color Doppler image whose RGB values ​​are within the red threshold range, delineate the reflux region based on these pixels, and then calculate the length of the reflux region based on the number of pixels in the reflux region along the reflux direction. In some embodiments, the determining module 220 can delineate the area displayed in red as the reflux region, and further determine the length of the reflux region of the target site through ultrasonic measurement.

[0060] In some embodiments, the length of the reflux region of the target site is the longest reflux region among the multiple frames of color Doppler images. For example, when the multiple frames of color Doppler images are all color Doppler images acquired during ultrasound imaging, the determining module 220 can determine the length of the longest reflux region of the target site among the multiple frames of color Doppler images based on the reflux information of each frame.

[0061] In some embodiments, the length of the reflux region in the target site is the average or weighted average of the lengths of the reflux regions in each frame of the multi-frame color Doppler images. For example, when the multi-frame color Doppler images are selected image frames with blood flow reflux, the determining module 220 can process the length of the reflux region in each frame of the multi-frame color Doppler images with reflux (e.g., calculate the average, calculate the weighted average, etc.) and use the processed length of the reflux region as the length of the reflux region in the target site.

[0062] In some embodiments, the determining module 220 can determine the degree of regurgitation at the target location based on the length of the regurgitation region of the target location and the length of the target location along the regurgitation direction. The length of the target location along the regurgitation direction refers to the maximum distance of the edge of the target location along the regurgitation direction, for example, it could be the maximum distance of the edge of the mitral valve along the regurgitation direction. For example, the determining module 220 can determine the degree of regurgitation at the target location based on the ratio of the length of the regurgitation region of the target location to the length of the target location along the regurgitation direction.

[0063] In some embodiments, when the ratio of the length of the backflow region of the target location to the length of the target location along the backflow direction is less than 1 / 3, the determining module 220 can determine that the backflow degree of the target location is mild backflow. In some embodiments, when the ratio of the length of the backflow region of the target location to the length of the target location along the backflow direction is in the range of 1 / 3 to 2 / 3, the determining module 220 can determine that the backflow degree of the target location is moderate backflow. In some embodiments, when the ratio of the length of the backflow region of the target location to the length of the target location along the backflow direction is greater than 2 / 3, the determining module 220 can determine that the backflow degree of the target location is severe backflow.

[0064] For example, such as Figure 4 In the schematic diagram of mitral regurgitation shown, when the regurgitation jet reaches the level of the valve annulus at position 410, the length of the regurgitation region reaches 1 / 3 of the left atrium, indicating mild regurgitation; when the regurgitation jet reaches the middle of the left atrium at position 420, the length of the regurgitation region reaches 1 / 2 of the left atrium, indicating moderate regurgitation; when the regurgitation jet reaches the roof of the left atrium at position 430, the length of the regurgitation region exceeds 2 / 3 of the left atrium, indicating severe regurgitation.

[0065] It should be understood that the above method for determining the degree of backflow is only illustrative. The determining module 220 can also determine the degree of backflow based on other backflow information (e.g., the area of ​​the backflow region, the width of the backflow region, the backflow velocity, etc.). For example, when the area of ​​the backflow region is less than 3 cm²... 2 If the ratio of the area of ​​the regurgitation region to the area of ​​the target site (e.g., when monitoring the degree of tricuspid regurgitation, the target site is the tricuspid valve orifice; when monitoring the degree of mitral regurgitation, the target site is the mitral valve orifice; when monitoring the degree of pulmonary valve regurgitation, the target site is the pulmonary valve orifice) is less than 20%, the determining module 220 can determine that the degree of regurgitation at the target site is mild regurgitation; when the area of ​​the regurgitation region is within 3 cm 2 -4.5cm 2 When the ratio of the area of ​​the reflux region within the range to the area of ​​the target part (the area of ​​the target part refers to the area occupied by the target part in the image frame, for example, the area occupied by the mitral lobe in the image frame) is in the range of 20%-50%, the determining module 220 can determine that the degree of reflux of the target part is moderate reflux; when the area of ​​the reflux region is greater than 4.5 cm 2If the ratio of the area of ​​the backflow region to the area of ​​the target location is greater than 50%, the determining module 220 can determine that the backflow degree of the target location is severe backflow. For example, when the backflow velocity is less than 150 cm / s, the determining module 220 can determine that the backflow degree of the target location is mild backflow; when the backflow velocity is in the range of 150 cm / s to 450 cm / s, the determining module 220 can determine that the backflow degree of the target location is moderate backflow; and when the backflow velocity is greater than 450 cm / s, the determining module 220 can determine that the backflow degree of the target location is severe backflow. For example, when the length of the backflow region is less than 20 mm, the determining module 220 can determine that the backflow degree of the target location is mild backflow; when the length of the backflow region is in the range of 20 mm to 45 mm, the determining module 220 can determine that the backflow degree of the target location is moderate backflow; and when the length of the backflow region is greater than 45 mm, the determining module 220 can determine that the backflow degree of the target location is severe backflow. For example, when the width ratio of the backflow region (the ratio of the width of the backflow region to the inner diameter of the target part) is between 20% and 40%, the determining module 220 can determine that the backflow degree of the target part is mild backflow; when the width ratio of the backflow region is between 40% and 60%, the determining module 220 can determine that the backflow degree of the target part is moderate backflow; and when the width ratio of the backflow region is greater than 60%, the determining module 220 can determine that the backflow degree of the target part is severe backflow. As another example, when the backflow pressure half-fall time is greater than 400ms, the determining module 220 can determine that the backflow degree of the target part is mild backflow; when the backflow pressure half-fall time is between 250ms and 400ms, the determining module 220 can determine that the backflow degree of the target part is moderate backflow; and when the backflow pressure half-fall time is less than 250ms, the determining module 220 can determine that the backflow degree of the target part is severe backflow.

[0066] In some embodiments, the determining module 220 can obtain multiple results of the backflow degree of the target location based on various backflow information, and combine the multiple results to obtain the backflow degree of the target location. For example, if the number of different results among the multiple results is the same, the result with the higher backflow degree is taken as the backflow degree of the target location. For example, if the backflow degree of the target location is determined to be mild backflow based on the width of the backflow region, and the backflow degree of the target location is determined to be moderate backflow based on the area of ​​the backflow region, then the combined result is a moderate backflow degree of the target location. As another example, if the number of different results among the multiple results is different, the result with the largest number is taken as the backflow degree of the target location. For example, if the backflow degree of the target location is determined to be mild backflow based on the length and width of the backflow region, and the backflow degree of the target location is determined to be moderate backflow based on the backflow velocity of the backflow region, then the combined result is a mild backflow degree of the target location.

[0067] In some embodiments, the determining module 220 can issue a backflow warning signal based on the degree of backflow at the target location. The warning signal can take the form of text, voice, image, pop-up window, indicator light, or any combination thereof. For example, when the backflow at the target location is mild, a text and / or voice prompt can be used to indicate mild backflow. As another example, when the backflow at the target location is moderate, a text, voice, and / or pop-up window prompt can be used to indicate moderate backflow. Yet another example, when the backflow at the target location is severe, a text, voice, pop-up window, and / or indicator light prompt can be used to indicate severe backflow.

[0068] Step 330: Generate a backflow information data map based on the backflow information of each frame of color Doppler image. In some embodiments, the backflow information data map may reflect the correspondence between the frame number of multiple frames of color Doppler images and the backflow information in each frame of color Doppler image. In some embodiments, step 330 may be performed by the processing device 120 or the generation module 230.

[0069] In some embodiments, the backflow information data graph can be a line graph, curve graph, bar chart, pie chart, etc., or any combination thereof. In some embodiments, the horizontal axis of the backflow information data graph can be the number of frames in the color Doppler image. In some embodiments, the vertical axis of the backflow information data graph can include one or more of the backflow information. For example, the vertical axis can include only the length of the backflow region, or the vertical axis can include both the length and area of ​​the backflow region. In some embodiments, the content included on the vertical axis of the backflow information data graph can be set by the system according to requirements and / or experience. In some embodiments, the content included on the vertical axis of the backflow information data graph can be set by the user.

[0070] In some embodiments, the generation module 230 can generate a reflux information data map in real time based on the reflux information of each frame of color Doppler image. Compared to the existing ultrasound imaging process, where the operator (e.g., a physician) needs to manually select a frame of color Doppler image for data measurement based on visual observation of the reflux situation, the real-time generation of reflux information data maps described in some embodiments of this specification can more automatically, in real time, and visually display the blood reflux situation at the target site, making the workflow of the ultrasound imaging process smoother.

[0071] Figure 5 This is a schematic diagram of an exemplary ultrasound imaging operation interface shown according to some embodiments of this specification. Figure 6 These are schematic diagrams illustrating exemplary ultrasound imaging operation interfaces according to some embodiments of this specification. Figure 5As shown, during imaging of a target area (e.g., the heart), the operator (e.g., a physician) does not need to manually stop at a particular frame. The ultrasound imaging interface can display in real time the color Doppler image of the target area (only a black and white image is shown in the example), the frame number (e.g., frame 165), and reflux information (e.g., the current frame's blood flow rate is 3.53 ml / s, the reflux velocity (i.e., "blood flow velocity" shown in the figure) is 1.00 m / s, the length of the reflux region (i.e., "blood flow length" shown in the figure) is 2.22 cm, the width of the reflux region (i.e., "blood flow width" shown in the figure) is 0.35 cm, and the area of ​​the reflux region (i.e., "blood flow area" shown in the figure) is 0.77 cm². 2 ) and a blood flow curve (i.e., a regurgitation information data graph) reflecting the relationship between blood flow and frame rate. For example Figure 5 As shown, the blood flow curve, reflecting the relationship between blood flow and frame rate, can display the magnitude of blood flow in Doppler images from multiple frames prior to the current frame in real time. When the operator clicks the "Switch Chart" button, Figure 5 Jump to Figure 6 The blood flow curve, which reflects the relationship between blood flow and frame rate, is converted into a blood flow velocity curve, which reflects the backflow velocity. For example... Figure 6 As shown, the Doppler images and regurgitation information displayed on the ultrasound imaging interface are consistent with... Figure 5 They are the same, the difference lies in the content displayed on the graph. In some embodiments, such as Figure 5 and Figure 6 As shown, the operator can click the "stop" button during the imaging process to stop the Doppler image and curve on the operation interface at a certain frame, while the Doppler image is still being acquired.

[0072] In some embodiments, based on user interaction with the backflow information data map, the generation module 230 can display a frame of color Doppler image of the target area and / or the backflow information corresponding to that frame of color Doppler image. For example, the operator can click the "Previous Frame" or "Next Frame" button below the backflow information data map to display an image of a certain frame and the associated backflow information. In some embodiments, the operator can click a node of a certain frame in the backflow information data map (e.g., the node of frame 165), at which time, such as Figure 6 As shown, the lower right corner of the interface displays the reflux information corresponding to the 165th frame of the color Doppler image, such as blood flow, blood flow velocity, length of the reflux region, width of the reflux region, area of ​​the reflux region, and degree of reflux; the middle part displays the 165th frame of color Doppler imaging.

[0073] Some embodiments of this application can (1) automatically identify the regurgitation of heart valves in real time, effectively identifying the regurgitation of the tricuspid, mitral, and aortic valves, as well as pathological regurgitation caused by atrioventricular septal defects; (2) detect extremely small regurgitation signals, making the detection more accurate; (3) display real-time data in the form of curves / line graphs, etc., and users can accurately locate key frames based on real-time data, improving detection efficiency; (4) click on nodes in curves / line graphs, etc. to open key frame previews, and the regurgitation ROI area, length, width, area, blood flow direction, velocity, etc. are displayed intuitively in the key frames; (5) automatically broadcast warnings for regurgitation signals, and store data for internal calculation to achieve quantitative analysis, assess the severity of valvular regurgitation, regurgitation of atrioventricular septal defects, etc., and perform medical classification (mild regurgitation, moderate regurgitation, and severe regurgitation), providing doctors with a basis for clinical diagnosis.

[0074] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0075] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0076] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0077] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0078] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0079] For each patent, patent application, patent application publication, and other material, such as articles, books, specifications, publications, and documents, referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0080] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A method for monitoring reflux, characterized in that, The method includes: Acquire color Doppler data of the target area; Based on the color Doppler data, the reflux information of each frame of the multi-frame color Doppler image is determined. The reflux information includes the length, width, and area of ​​the reflux region, the direction of blood flow within the reflux region, and the velocity of blood flow within the reflux region; and Based on the backflow information of each frame of color Doppler image, a backflow information data map is generated in real time. The backflow information data map reflects the correspondence between the frame number of the multi-frame color Doppler images and the backflow information in each frame of color Doppler image. The horizontal axis of the backflow information data map is the frame number of the color Doppler image, and the vertical axis of the backflow information data map includes the backflow information.

2. The method according to claim 1, characterized in that, The method further includes: The degree of backflow at the target location is determined based on the backflow information data map.

3. The method according to claim 2, characterized in that, Determining the degree of backflow at the target location based on the backflow information data map includes: By performing image processing on multiple frames of color Doppler images in the backflow information data map, the length, width, area, and backflow velocity of the backflow region are determined; The degree of backflow at the target location is determined based on the length, width, area, and backflow velocity of the backflow region.

4. The method according to claim 3, characterized in that, Determining the degree of backflow at the target location based on the backflow information data map includes: Based on the backflow information in the multi-frame color Doppler images, the length of the backflow region at the target location is determined; and The degree of backflow at the target location is determined based on the length of the backflow region at the target location and the length of the target location along the backflow direction, including: When the ratio of the length of the backflow region of the target location to the length of the target location along the backflow direction is less than 1 / 3, the degree of backflow of the target location is determined to be mild backflow. When the ratio of the length of the backflow region of the target location to the length of the target location along the backflow direction is in the range of 1 / 3 to 2 / 3, the degree of backflow of the target location is determined to be moderate backflow. When the ratio of the length of the backflow region of the target location to the length of the target location along the backflow direction is greater than 2 / 3, the degree of backflow of the target location is determined to be severe backflow.

5. The method according to claim 3, characterized in that, Determining the degree of backflow at the target location based on the backflow information data map includes: Based on the backflow information in the multi-frame color Doppler images, the width of the backflow region at the target location is determined; and The degree of backflow at the target location is determined based on the width of the backflow region and the inner diameter of the target location, including: When the width of the backflow area is within the range of 20%-40%, the backflow degree of the target part is determined to be mild backflow, wherein the width of the backflow area is the ratio of the width of the backflow area to the inner diameter of the target part. When the width of the backflow area accounts for 40%-60% of the total area, the degree of backflow at the target location is determined to be moderate backflow. When the width of the backflow area accounts for more than 60%, the backflow degree of the target part is determined to be severe backflow.

6. The method according to claim 3, characterized in that, Determining the degree of backflow at the target location based on the backflow information data map includes: Based on the reflux information in the multi-frame color Doppler images, the area of ​​the reflux region at the target location is determined; and The degree of backflow at the target location is determined based on the area of ​​the backflow region at the target location and the area of ​​the target location itself, including: When the area of ​​the reflux region is less than 3cm 2 If the ratio of the area of ​​the reflux region to the area of ​​the target part is less than 20%, the degree of reflux at the target part is determined to be mild reflux. When the area of ​​the reflux region is 3cm 2 -4.5cm 2 When the ratio of the area within the range or the area of ​​the backflow region to the area of ​​the target part is in the range of 20%-50%, the degree of backflow of the target part is determined to be moderate backflow. When the area of ​​the reflux region is greater than 4.5 cm 2 If the ratio of the area of ​​the reflux region to the area of ​​the target part is greater than 50%, the reflux degree of the target part is determined to be severe reflux.

7. The method according to claim 3, characterized in that, Determining the degree of backflow at the target location based on the backflow information data map includes: The backflow velocity is determined based on the backflow information in the multi-frame color Doppler images; and Determining the degree of backflow at the target location based on the backflow velocity includes: When the backflow velocity is less than 150 cm / s, the backflow degree of the target location is determined to be mild backflow; When the backflow velocity is in the range of 150cm / s to 450cm / s, the degree of backflow at the target location is determined to be moderate backflow. When the backflow velocity is greater than 450 cm / s, the backflow degree of the target location is determined to be severe backflow.

8. The method according to claim 2, characterized in that, The method further includes: A backflow warning signal is issued based on the degree of backflow at the target location.

9. The method according to claim 1, characterized in that, The method further includes: displaying a frame of color Doppler image of the target region based on the user's interaction with the backflow information data map, wherein the backflow information is displayed on the color Doppler image.

10. The method according to claim 1, characterized in that, The backflow information data map is obtained based on the image frames in the multi-frame color Doppler images where the backflow information is greater than a threshold.

11. The method according to claim 1, characterized in that, The step of determining the backflow information of each frame of color Doppler image in the multi-frame color Doppler images based on the color Doppler data includes: Based on the RGB values ​​of the pixels in the color Doppler data, the backflow information of each frame of the color Doppler image in the multi-frame color Doppler image is determined.

12. A backflow monitoring system, characterized in that, The system includes: The acquisition module is used to acquire color Doppler data of the target area; The determining module is used to determine the reflux information of each frame of color Doppler images in a multi-frame color Doppler image set based on the color Doppler data. The reflux information includes the length, width, and area of ​​the reflux region, the direction of blood flow in the reflux region, and the velocity of blood flow in the reflux region. The generation module is used to generate a backflow information data map in real time based on the backflow information of each frame of color Doppler image. The backflow information data map reflects the correspondence between the frame number of the multi-frame color Doppler images and the backflow information in each frame of color Doppler image. The horizontal axis of the backflow information data map is the frame number of the color Doppler image, and the vertical axis of the backflow information data map includes the backflow information.

13. A backflow monitoring device, characterized in that, The device includes: At least one storage medium storing computer instructions; and At least one processor executes the computer instructions to implement the method of any one of claims 1 to 11.

14. A computer-readable storage medium storing computer instructions that, when read by a computer, execute the method as described in any one of claims 1 to 11.

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