Method, device and equipment for simulating myocardial blood flow

Abstract

The invention relates to a method, a device and equipment for simulating myocardial blood flow. The method comprises the steps that an angiography image containing a coronary artery and a left ventricle adjacent to the coronary artery is obtained, the angiography image comprises at least one first area and at least one second area, the at least one first area is located in a myocardial area of the left ventricle, and the at least one second area is located in a lumen area of the coronary artery; for the at least one first area, obtaining a first time density curve to obtain the maximum slope of the first time density curve; for at least one second area, acquiring a second time density curve to obtain a maximum enhancement value of the second time density curve; and determining the myocardial blood flow according to the maximum slope and the maximum enhancement value. According to the invention, the health risk of a patient is reduced, the medical cost is reduced, and the efficiency of acquiring myocardial blood flow is improved.

Description

Technical Field

[0002] The present disclosure relates to the field of CT imaging technology, and in particular, to a method for simulating myocardial blood flow, a device for simulating myocardial blood flow, and an electronic device. Background Art

[0004] Coronary heart disease is one of the diseases with the highest mortality rate globally. In recent years, with the continuous increase in the incidence and mortality rate of coronary heart disease, cardiovascular diseases have become a major public health problem. Coronary computed tomography angiography (CTA), as a non-invasive imaging method, has been widely used in the assessment of the degree and efficacy of coronary artery stenosis in patients with coronary heart disease. However, it cannot provide accurate quantitative information on coronary hemodynamics and myocardial blood flow (MBF). Therefore, it is still necessary to perform examinations such as myocardial CT perfusion (CTP) to measure myocardial blood flow and myocardial viability, etc.

[0005] However, the contrast agent dose used in CTP is relatively large and the radiation is relatively strong, thus causing relatively large health risks. Moreover, the time consumed for CTP examination is relatively long.

[0006] Therefore, there is an urgent need for a method for simulating myocardial blood flow, which needs to reduce the health risks of patients, reduce medical costs, and improve the efficiency of obtaining myocardial blood flow. Summary of the Invention

[0008] In view of this, according to one aspect of the present disclosure, there is provided a method for simulating myocardial blood flow, including: obtaining an angiographic image including a coronary artery and a left ventricle adjacent to the coronary artery, the angiographic image including at least one first region and at least one second region, wherein at least one first region is located in the myocardial region of the left ventricle, and at least one second region is located in the lumen region of the coronary artery; for at least one first region, obtaining a first time-density curve to obtain the maximum slope of the first time-density curve; for at least one second region, obtaining a second time-density curve to obtain the maximum enhancement value of the second time-density curve; and determining the myocardial blood flow according to the maximum slope and the maximum enhancement value.

[0009] According to another aspect of the present disclosure, there is provided an apparatus for simulating myocardial blood flow, the apparatus comprising: a first unit configured to acquire an angiographic image including a coronary artery and a left ventricle adjacent to the coronary artery, the angiographic image including at least one first region and at least one second region, wherein at least one first region is located in the myocardial region of the left ventricle and at least one second region is located in the lumen region of the coronary artery; a second unit configured to acquire a first time-density curve for at least one first region to obtain a maximum slope of the first time-density curve; a third unit configured to acquire a second time-density curve for at least one second region to obtain a maximum enhancement value of the second time-density curve; and a fourth unit configured to determine myocardial blood flow based on the maximum slope and the maximum enhancement value.

[0010] According to still another aspect of the present disclosure, there is provided an electronic device, comprising: at least one processor; and at least one memory communicatively connected to the at least one processor; wherein the at least one memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute a method for simulating myocardial blood flow.

[0011] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings exemplarily illustrate embodiments and constitute a part of the specification, and are used together with the written description of the specification to explain the exemplary embodiments of the embodiments. The illustrated embodiments are for illustrative purposes only and do not limit the scope of the claims. In all the drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0014] Embodiments of the present disclosure will be described in detail below with reference to the drawings, making the above and other features and advantages of the present disclosure clearer to those of ordinary skill in the art. In the drawings:

[0015] Figure 1 shows a flowchart of a method for simulating myocardial blood flow according to an embodiment of the present disclosure;

[0016] Figure 2 shows Figure 1 a flowchart of a partial process of the method for simulating myocardial blood flow in

[0017] Figure 3 shows Figure 1 a flowchart of a partial process of the method for simulating myocardial blood flow in

[0018] Figure 4 The flowchart of a treatment plan recommendation method according to an embodiment of the present disclosure is shown;

[0019] Figure 5 The schematic diagram of generating an angiogram by applying the method of simulating myocardial blood flow according to an embodiment of the present disclosure is shown;

[0020] Figure 6A - Figure 6B The schematic diagram of obtaining a myocardial blood perfusion image by applying the method of simulating myocardial blood flow according to an embodiment of the present disclosure is shown;

[0021] Figure 7 The structural block diagram of a device for simulating myocardial blood flow according to an embodiment of the present disclosure is shown; and

[0022] Figure 8 The block diagram of an exemplary electronic device according to an embodiment of the present disclosure is shown. Detailed implementation manners

[0024] The following makes an illustration of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0025] In the present disclosure, unless otherwise specified, the terms "first", "second", etc. are used to describe various elements and are not intended to limit the positional relationship, temporal relationship or importance relationship of these elements. Such terms are only used to distinguish one element from another. In some examples, the first element and the second element may refer to the same instance of the element, and in certain cases, based on the description of the context, they may also refer to different instances.

[0026] In the description of various examples in the present disclosure, the terms used are only for the purpose of describing specific examples and are not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the element may be one or more. In addition, the term "and / or" used in the present disclosure covers any one of the listed items and all possible combinations.

[0027] As described above, professionals can use invasive coronary angiography or CT myocardial perfusion imaging to obtain information on myocardial blood flow in patients, so as to evaluate the blood flow function of patients. In some scenarios, patients do not meet the conditions for performing the above two examinations. For example, the patient's physical condition does not allow the injection of a large dose of contrast agent or invasive examination, or the patient's condition is urgent and cannot wait for the results of perfusion imaging. In addition, the above two examination methods cannot accurately reflect early ischemia or microvascular ischemia.

[0028] Based on this, the present disclosure provides a method for simulating myocardial blood flow, a treatment plan recommendation method, a device for simulating myocardial blood flow, and an electronic device.

[0029] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0030] Figure 1 The flowchart of the method 100 for simulating myocardial blood flow according to an embodiment of the present disclosure is shown.

[0031] Refer to Figure 1 , the method 100 for simulating myocardial blood flow includes:

[0032] Step S110, obtain an angiography image including the coronary artery and the left ventricle adjacent to the coronary artery, the angiography image including at least one first region and at least one second region, wherein at least one first region is located in the myocardial region of the left ventricle, and at least one second region is located in the lumen region of the coronary artery;

[0033] Step S130, for at least one first region, obtain a first time-density curve to obtain the maximum slope of the first time-density curve;

[0034] Step S140, for at least one second region, obtain a second time-density curve to obtain the maximum enhancement value of the second time-density curve; and

[0035] Step S150, determine the myocardial blood flow according to the maximum slope and the maximum enhancement value.

[0036] The method 100 provides a method for simulating myocardial blood flow. Specifically, the method 100 obtains time-density curves from specific regions of coronary CT angiography images to simulate myocardial blood flow.

[0037] The time-density curve (TDC) is a graph that reflects the change in CT values over time in a specific region of a patient, such as a blood vessel or tissue. It typically uses time as the horizontal axis and CT values as the vertical axis to reflect the density changes in a specific region at different time points. For example, in CT myocardial perfusion imaging, discrete CT value data at multiple time points are collected and fitted into a time-density curve. Still taking CT myocardial perfusion imaging as an example, to further calculate myocardial blood flow, it is necessary to simultaneously measure the time-density curve of the coronary artery lumen region of the patient and the time-density curve of the left ventricular myocardial region of the patient. Both of these time-density curves need to completely include the entire process from the CT value rising to the peak and then falling to becoming stable. Further, through the maximum slope of the time-density curve of the left ventricular myocardial region and the maximum enhancement value of the time-density curve of the coronary artery lumen region, the myocardial blood flow can be calculated.

[0038] In the example of step S110, similar to the above-mentioned CT myocardial perfusion imaging, method 100 also needs to simultaneously obtain angiography images including at least one myocardial region located in the left ventricle and at least one lumen region located in the coronary artery.

[0039] Figure 5 Shows a schematic diagram of generating an angiography image by applying the method for simulating myocardial blood flow according to an embodiment of the present disclosure. As Figure 5 shown, the angiography image obtained by method 100 can be a three-dimensional reconstructed image including the myocardial region of the left ventricle and the lumen region of the coronary artery.

[0040] According to some embodiments of the present disclosure, after step S110, it may further include step S120 of obtaining at least one first region of interest and at least one second region of interest based on the angiography image.

[0041] Figure 3 Shows Figure 1 a flowchart of a partial process of the method for simulating myocardial blood flow in Figure 3 shown, step S120 further includes:

[0042] Step S310, preprocessing the angiography image to obtain the preprocessed angiography image;

[0043] Step S320, segmenting the preprocessed angiography image into the myocardial region of the left ventricle and the lumen region of the coronary artery;

[0044] Step S330, extracting at least one first region of interest as at least one first region in the myocardial region of the left ventricle; and

[0045] Step S340: In the lumen region of the coronary artery, extract at least one second region of interest as at least one second region.

[0046] In the example of step S310, the preprocessing of the angiography image includes noise reduction such as Gaussian filtering and median filtering, image registration, resampling, normalization processing, etc. Through the above preprocessing methods, the image quality of the angiography image can be improved, providing a reliable basis for the subsequent calculation of myocardial blood flow.

[0047] Based on this, in the example of step S320, the preprocessed angiography image is segmented into the myocardial region of the left ventricle and the lumen region of the coronary artery, so as to obtain the time density curve of the lumen region of the patient's coronary artery and the time density curve of the myocardial region of the patient's left ventricle respectively.

[0048] Furthermore, in the examples of steps S330 and S340, the first region and the second region are determined by extracting regions of interest (ROIs) from the lumen region of the coronary artery and the myocardial region of the left ventricle respectively. Among them, the region of interest can be automatically identified or demarcated by professionals according to clinical experience and relevant knowledge. The purposes of doing so are as follows: First, the demarcation of the ROI reduces unnecessary calculations and improves calculation efficiency. Especially when dealing with a large amount of data, time and computing resources can be saved; Second, the demarcation of the ROI can exclude the interference of irrelevant regions and improve the accuracy of diagnosis; Third, the demarcation of the ROI helps to standardize the analysis process and ensure the comparability of comparisons at different time points or among different patients; Finally, in dynamic monitoring, demarcating the ROI can track the changes in specific regions, such as treatment effects or disease progression.

[0049] Through the above step S120, that is, steps S310 - S340, the obtained angiography image is preprocessed, which is beneficial to accurately simulate myocardial blood flow. In addition, by extracting regions of interest and using them as the first region and the second region, it helps to generate subsequent time density curves and simplify the calculation of myocardial blood flow.

[0050] Continue to refer to Figure 1 , in the example of step S130, generate the first time density curve of the first region and calculate the maximum slope of the first time density curve, and in the example of step S140, generate the second time density curve of the second region and calculate the maximum enhancement value of the second time density curve.

[0051] As described above, the time-density curves in CT myocardial perfusion imaging need to completely include the entire process of the CT value rising to the peak and then falling to a stable state. However, this will result in a greater radiation dose and a longer data acquisition time. To solve this problem, the time-density curves in the embodiments of the present disclosure are sparse sampling. That is to say, in step S130, for the first region and the second region, only data at specific time points or time periods are collected, thereby forming two "incomplete" time-density curves.

[0052] In some embodiments of the present disclosure, the start time of collecting the time-density curve can be set by setting a trigger value. Specifically, the first time-density curve starts to be collected from the first trigger time, and the first trigger time is the time when the first monitored CT value of at least one first region first exceeds the preset first trigger value; and the second time-density curve starts to be collected from the second trigger time, and the second trigger time is the time when the second monitored CT value of at least one second region first exceeds the preset second trigger value. The time after a certain interval after injecting the contrast agent can also be used as the start time of collection.

[0053] Similarly, the stop time of collecting the time-density curve can be set by setting a threshold value. Specifically, the first time-density curve stops being collected at the first cut-off time, and the first cut-off time is configured to be the time when the first monitored CT value of at least one first region first exceeds the preset first threshold value; the second time-density curve stops being collected from the second cut-off time, and the second cut-off time is configured to be the time when the second monitored CT value of at least one second region first exceeds the preset second threshold value. The time after a certain interval after starting the collection can also be set as the stop time of collection.

[0054] Figure 2 shows Figure 1 a flowchart of a partial process of the method for simulating myocardial blood flow in. As Figure 2 shown, in step S130, the maximum slope of the first time-density curve is determined by the following steps:

[0055] S210. For multiple first sub-segments of the first time-density curve, calculate the first slope of each first sub-segment; and

[0056] S220. Determine the maximum slope calculated among the multiple first sub-segments as the maximum slope, where the multiple first sub-segments are composed of the connections between every two adjacent first monitored CT values of at least one first region during the angiography process.

[0057] In the example of step S210, it can be seen that the first time density curve is composed of first sub-segments between multiple adjacent data points. Compared with fitting dozens of data points into a time density curve in traditional CT myocardial perfusion imaging, the first time density curve in the embodiments of the present disclosure is directly composed of multiple first sub-segments, so that the first slope of each first sub-segment can be calculated simply and quickly, which is beneficial to improving the efficiency of simulating myocardial blood flow.

[0058] In the example of step S220, the maximum value among the first slopes of multiple first sub-segments is directly used as the maximum slope, so as to quickly obtain the maximum slope of the first time density curve.

[0059] In addition, for step S140, the difference between the maximum value and the minimum value among multiple second monitoring CT values of at least one second region during the angiography process can be calculated as the maximum enhancement value, so as to simply calculate the maximum enhancement value.

[0060] Based on this, in the example of step S150, the myocardial blood flow of the coronary artery is determined according to the above maximum slope and the above maximum enhancement value.

[0061] Since the method of the embodiments of the present disclosure simulates the myocardial blood flow of the coronary artery through the CT angiography data of the coronary artery and the left ventricle adjacent to the coronary artery, that is, angiography images, the first time density curve and the second time density curve, the patient does not need to be subjected to invasive examinations and does not need to inject a large dose of contrast agent, thus reducing the related health risks and complications. The method of the embodiments of the present disclosure directly uses the maximum slope and the maximum enhancement value of the time density curve, so that an estimated value of myocardial blood flow can be quickly provided, making it applicable to real-time clinical decision-making, especially beneficial to initially evaluating the conditions of patients with acute coronary heart disease or myocardial ischemia in emergency situations. In addition, since coronary CT angiography has been widely used in the clinical practice of coronary artery disease assessment, the method of the embodiments of the present disclosure is easy to be combined with the existing clinical workflow, thus reducing the application cost and the difficulty of popularization.

[0062] In some embodiments of the present disclosure, the myocardial blood flow is calculated through a weighted linear combination of the maximum slope and the maximum enhancement value. Compared with calculating the myocardial blood flow using a complex hemodynamic model in CT myocardial perfusion imaging, the method of the embodiments of the present disclosure simplifies the calculation process significantly through a linear formula including the maximum slope and the maximum enhancement value, and provides a relatively accurate preliminary estimate of the myocardial blood flow.

[0063] Specifically, the following empirical formula can be used to calculate the myocardial blood flow:

[0064] MBF = (k1×S + k2×E) + b

[0065] Among them, MBF is myocardial blood flow, S is the maximum slope of the first time density curve, and E is the maximum enhancement value of the second time density curve. k1, k2, and b are coefficients determined according to clinical data or experiments, and k1, k2, and b can be constants.

[0066] The linear empirical formula as described above does not require a large amount of computing resources or detailed anatomical and physiological information, and provides an objective and reproducible assessment of myocardial blood flow, thereby improving the accuracy and consistency of disease diagnosis relying on myocardial blood flow and reducing uncontrollable variations related to subjective interpretation in clinical practice.

[0067] In some embodiments of the present disclosure, the region of myocardial ischemia can be determined through the simulated myocardial blood flow. For example, the region of myocardial ischemia can be displayed in the obtained angiography image with a color different from that of the normal myocardial region or a different CT value, or the region of myocardial ischemia can be marked in the angiography image with a special marking symbol. The region of myocardial ischemia, the degree and proportion of myocardial ischemia, etc. can also be described in words.

[0068] Figure 6A - Figure 6B The schematic diagram shows the acquisition of a myocardial blood perfusion image by applying the method of simulating myocardial blood flow according to the embodiments of the present disclosure. As Figure 6A - Figure 6B shown, in some embodiments of the present disclosure, a visualization map of the coronary artery blood flow distribution can be generated based on the simulated myocardial blood flow; and / or the angiography image can be image-fused with the myocardial blood flow to generate a myocardial perfusion image. Specifically, as Figure 6A shown, the visualization map of the coronary artery blood flow distribution can be presented in the form of a bull's-eye diagram. In the bull's-eye diagram, the percentage change in wall thickness, myocardial perfusion, and dynamic behaviors such as the velocity, displacement, strain, strain rate, and rotation angle of myocardial tissue movement in different systolic and diastolic phases of the myocardium are represented by different colors or gray levels, so as to intuitively, quickly, and accurately determine the severity of myocardial damage and the scope of lesions in different segmental regions of the heart, and comprehensively evaluate the systolic and diastolic function changes of the whole heart and local regions.

[0069] The angiography image can be image-fused with the myocardial blood flow. As Figure 6B shown, the Figure 6B fusion image is based on the tomographic two-dimensional image of the angiography image and the myocardial blood flow at that position. The three-dimensional reconstructed angiography image as described above can also be fused with the myocardial blood flow to obtain a dynamic myocardial perfusion image.

[0070] According to another aspect of the present disclosure, a treatment plan recommendation method is provided.

[0071] Figure 4 The flowchart of a treatment plan recommendation method 400 according to an embodiment of the present disclosure is shown. As Figure 4 shown, the treatment plan recommendation method 400 includes:

[0072] Step S410: Obtain the myocardial blood flow of the target object simulated by the method for simulating myocardial blood flow;

[0073] Step S420: Generate a data output for assisting in formulating a treatment plan based on the myocardial blood flow and the individual information of the target object.

[0074] In the example of step S410, the method 100 described Figure 1 is adopted to obtain the myocardial blood flow of the target object. Thus, the operations, features, and advantages described above for method 100 also apply to method 400. For the sake of brevity, some operations, features, and advantages are not described herein again.

[0075] In the example of step S420, the individual information of the target object may include the basic information of the target object, such as information about the target object's height, weight, blood type, family history, allergy history, etc.; the individual information of the target object may also include the pathological information of the target object, such as the electrocardiogram information of the target object, chest X-ray examination, etc.; the individual information of the target object may further include the subjective information of the target object, such as the treatment method preference of the target object, the treatment compliance of the target object, the psychological state of the target object, etc.

[0076] Based on the above individual information and myocardial blood flow of the target object, a preliminary treatment plan can be automatically generated. The treatment plan may include suggestions for the selection of treatment methods, such as which drugs to use, whether to perform surgical operations or interventional treatments, and other auxiliary treatment means; the treatment plan may also include suggestions for lifestyle interventions, such as diet adjustment, exercise plans, smoking cessation and alcohol abstinence, etc.; the treatment plan may further include suggestions for psychological interventions to help the target object cope with the psychological pressure brought by the disease.

[0077] The above description does not limit step S420. According to actual needs, an appropriate form and content can be selected to generate the data output of the treatment plan.

[0078] According to another aspect of the present disclosure, a device for simulating myocardial blood flow is provided.

[0079] Figure 7 The structural block diagram of a device 700 for simulating myocardial blood flow according to an embodiment of the present disclosure is shown. As Figure 7 shown, the device 700 for simulating myocardial blood flow includes:

[0080] A first unit 710 configured to acquire an angiographic image including a coronary artery and a left ventricle adjacent to the coronary artery, the angiographic image including at least one first region and at least one second region, wherein at least one first region is located in a myocardial region of the left ventricle and at least one second region is located in a lumen region of the coronary artery;

[0081] A second unit 720 configured to acquire, for at least one first region, a first time density curve to obtain a maximum slope of the first time density curve;

[0082] A third unit 730 configured to acquire, for at least one second region, a second time density curve to obtain a maximum enhancement value of the second time density curve; and

[0083] A fourth unit 740 configured to determine myocardial blood flow based on the maximum slope and the maximum enhancement value.

[0084] It should be understood that Figure 7 each unit of the device 700 shown in Figure 1 may correspond to the steps S110 and S130 - S150 in the method 100 described with reference to

[0085] Thus, the operations, features, and advantages described above for the method 100 also apply to the device 700 and its included units. For the sake of brevity, certain operations, features, and advantages are not described herein again.

[0086] It should also be understood that various techniques may be described herein in the general context of software - hardware elements or program units. Regarding the above Figure 7The various units described can be implemented in hardware or in hardware in combination with software and / or firmware. For example, these units can be implemented as computer program code / instructions configured to be executed in one or more processors and stored in a computer-readable storage medium. Alternatively, these units can be implemented as hardware logic / circuits. For example, in some embodiments, one or more of the first unit 710, the second unit 720, the third unit 730, and the fourth unit 740 can be implemented together in a System on Chip (SoC). The SoC can include an integrated circuit chip (which includes one or more components such as a processor (e.g., a Central Processing Unit (CPU), a microcontroller, a microprocessor, a Digital Signal Processor (DSP), etc.), a memory, one or more communication interfaces, and / or other circuits), and can optionally execute the received program code and / or include embedded firmware to perform functions.

[0087] According to another aspect of the present disclosure, there is provided an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for simulating myocardial blood flow as described above.

[0088] According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing a computer program, the computer program being for causing a computer to execute the method for simulating myocardial blood flow as described above.

[0089] According to another aspect of the present disclosure, there is provided a computer program product, including a computer program, the computer program implementing the method for simulating myocardial blood flow as described above when executed by a processor.

[0090] Figure 8 is a block diagram showing an example of an electronic device 800 according to an exemplary embodiment of the present disclosure. It should be noted that Figure 8 the structure shown is only an example, and according to a specific implementation manner, the electronic device of the present disclosure may only include Figure 8 one or more of the components shown.

[0091] The electronic device 800 can be, for example, a general-purpose computer (such as various computers like a laptop computer, a tablet computer, etc.), a mobile phone, or a personal digital assistant. According to some embodiments, the electronic device 800 can be a cloud computing device and an intelligent device. According to some embodiments, the electronic device 800 can be an X-ray imaging device, such as a computed tomography (CT) device.

[0092] According to some embodiments, the electronic device 800 may be configured to process at least one of images, text, and audio, and transmit the processing result to an output device for providing to the user. The output device may be, for example, a display screen, a device including a display screen, or a sound output device such as headphones, speakers, or oscillators. For example, the electronic device 800 may be configured to perform object detection on an image, transmit the object detection result to a display device for display, and the electronic device 800 may also be configured to perform enhancement processing on the image and transmit the enhancement result to the display device for display. The electronic device 800 may also be configured to recognize text in the image, transmit the recognition result to the display device for display and / or convert the recognition result into sound data and transmit it to a sound output device for playback. The electronic device 800 may also be configured to recognize and process audio, transmit the recognition result to the display device for display and / or convert the processing result into sound data and transmit it to a sound output device for playback.

[0093] The electronic device 800 may include an image processing circuit 803, and the image processing circuit 803 may be configured to perform various image processing operations on images. The image processing circuit 803 may, for example, be configured to perform at least one of the following image processing operations on an image: noise reduction of the image, normalization processing of the image, registration of the image, geometric correction of the image, feature extraction of the image, detection and / or recognition of an object in the image, enhancement processing of the image, and detection and / or recognition of text included in the image, etc.

[0094] The electronic device 800 may further include a text recognition circuit 804, and the text recognition circuit 804 is configured to perform text detection and / or recognition (such as OCR processing) on a text area in an image to obtain text data. The text recognition circuit 804 may be implemented, for example, by a dedicated chip. The electronic device 800 may further include a sound conversion circuit 805, and the sound conversion circuit 805 is configured to convert the text data into sound data. The sound conversion circuit 805 may be implemented, for example, by a dedicated chip.

[0095] The electronic device 800 may further include an audio processing circuit 806, and the audio processing circuit 806 is configured to convert audio into text to obtain text data corresponding to the audio. The audio processing circuit 806 may also be configured to process the text data corresponding to the audio, and may, for example, include keyword extraction, intent recognition, intelligent recommendation, and intelligent Q&A, etc. The audio processing circuit 806 may be implemented, for example, by a dedicated chip. The sound conversion circuit 805 may also be configured to convert the audio processing result into sound data to be applicable to application scenarios such as voice assistants or virtual customer service.

[0096] One or more of the various circuits described above (such as the image processing circuit 803, the character recognition circuit 804, the voice conversion circuit 805, and the audio processing circuit 806) may use custom hardware and / or may be implemented using hardware, software, firmware, middleware, microcode, a hardware description language, or any combination thereof. For example, one or more of the various circuits described above may be implemented by programming hardware (such as a programmable logic circuit including a field programmable gate array (FPGA) and / or a programmable logic array (PLA)) using assembly language or a hardware programming language (such as VERILOG, VHDL, C++) based on the logic and algorithms of the present disclosure.

[0097] According to some embodiments, the electronic device 800 may further include an output device 807, and the output device 807 may be any type of device for presenting information, and may include but is not limited to a display screen, a terminal with a display function, headphones, speakers, a vibrator, and / or a printer, etc.

[0098] According to some embodiments, the electronic device 800 may further include an input device 808, and the input device 808 may be any type of device for inputting information to the electronic device 800, and may include but is not limited to various sensors, a mouse, a keyboard, a touch screen, buttons, a joystick, a microphone, and / or a remote control, etc.

[0099] According to some embodiments, the electronic device 800 may further include a communication device 809, and the communication device 809 may be any type of device or system that enables communication with external devices and / or with a network, and may include but is not limited to a modem, a network card, an infrared communication device, a wireless communication device, and / or a chipset, such as a Bluetooth device, an 802.11 device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0100] According to some embodiments, the electronic device 800 may further include a processor 801. The processor 801 may be any type of processor, and may include but is not limited to one or more general-purpose processors and / or one or more dedicated processors (such as a special processing chip). The processor 801 may be, for example, but not limited to a central processing unit CPU, a graphics processing unit GPU, or various dedicated artificial intelligence (AI) computing chips, etc.

[0101] The electronic device 800 may also include a working memory 802 and a storage device 811. The processor 801 may be configured to be able to obtain and execute computer-readable instructions stored in the working memory 802, the storage device 811, or other computer-readable media, such as the program code of the operating system 802a, the program code of the application program 802b, and the like. The working memory 802 and the storage device 811 are examples of computer-readable storage media for storing instructions, and the stored instructions can be executed by the processor 801 to implement the various functions described above. The working memory 802 may include both volatile memory and non-volatile memory (such as RAM, ROM, etc.). The storage device 811 may include a hard disk drive, a solid-state drive, a removable medium, including external and removable drives, memory cards, flash memory, floppy disks, optical discs (such as CDs, DVDs), storage arrays, network-attached storage, storage area networks, and the like. The working memory 802 and the storage device 811 may both be collectively referred to as memory or computer-readable storage media herein, and may be non-transitory media capable of storing computer-readable, processor-executable program instructions as computer program code, and the computer program code may be executed by the processor 801 as a specific machine configured to implement the operations and functions described in the examples herein.

[0102] According to some embodiments, the processor 801 may control and schedule at least one of the image processing circuit 803, the character recognition circuit 804, the voice conversion circuit 805, the audio processing circuit 806, and various other devices and circuits included in the electronic device 800. According to some embodiments, Figure 8 At least some of the various components described above may be interconnected and / or communicate with each other via the bus 810.

[0103] Software elements (programs) may be located in the working memory 802, including but not limited to the operating system 802a, one or more application programs 802b, drivers, and / or other data and code.

[0104] According to some embodiments, the instructions for performing the foregoing control and scheduling may be included in the operating system 802a or one or more application programs 802b.

[0105] According to some embodiments, the instructions for performing the method steps described in the present disclosure may be included in one or more application programs 802b, and each module of the electronic device 800 may be implemented by the processor 801 reading and executing the instructions of one or more application programs 802b. In other words, the electronic device 800 may include a processor 801 and a memory (such as a working memory 802 and / or a storage device 811) storing a program, the program including instructions which, when executed by the processor 801, cause the processor 801 to perform the methods described in various embodiments of the present disclosure.

[0106] According to some embodiments, some or all of the operations performed by at least one of the image processing circuit 803, the character recognition circuit 804, the voice conversion circuit 805, and the audio processing circuit 807 may be implemented by the processor 801 reading and executing the instructions of one or more application programs 802b.

[0107] The executable code or source code of the instructions of the software element (program) may be stored in a non-transitory computer-readable storage medium (such as the storage device 811), and when executed, may be loaded into the working memory 802 (possibly compiled and / or installed). Thus, the present disclosure provides a computer-readable storage medium storing a program, the program including instructions which, when executed by a processor of an electronic device, cause the electronic device to perform the methods described in various embodiments of the present disclosure. According to another embodiment, the executable code or source code of the instructions of the software element (program) may also be downloaded from a remote location.

[0108] It should also be understood that various modifications can be made according to specific requirements. For example, custom hardware may also be used, and / or each circuit, unit, module, or component may be implemented using hardware, software, firmware, middleware, microcode, a hardware description language, or any combination thereof. For example, some or all of the circuits, units, modules, or components included in the disclosed methods and devices may be implemented by programming hardware (such as programmable logic circuits including field-programmable gate arrays (FPGAs) and / or programmable logic arrays (PLAs)) using logic and algorithms according to the present disclosure, with an assembly language or a hardware programming language (such as VERILOG, VHDL, C++).

[0109] According to some embodiments, the processor 801 in the electronic device 800 may be distributed over a network. For example, one processor may be used to perform some processing, while another processor located far from the one processor may perform other processing at the same time. Other modules of the electronic device 800 may be similarly distributed. In this way, the electronic device 800 may be interpreted as a distributed computing system that performs processing at multiple locations. The processor 801 of the electronic device 800 may also be a processor of a cloud computing system or a processor incorporating a blockchain.

[0110] Although embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above methods, systems, and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but is only defined by the authorized claims and their equivalent scope. Various elements in the embodiments or examples may be omitted or replaced by their equivalent elements. In addition, the steps may be executed in an order different from that described in the present disclosure. Further, the various elements in the embodiments or examples may be combined in various ways. Importantly, with the evolution of technology, many of the elements described herein may be replaced by equivalent elements that emerge after the present disclosure.

Claims

1. A method for simulating myocardial blood flow, comprising: Obtaining an angiographic image including a coronary artery and a left ventricle adjacent to the coronary artery, the angiographic image including at least one first region and at least one second region, wherein the at least one first region is located in the myocardial region of the left ventricle, and the at least one second region is located in the lumen region of the coronary artery; For the at least one first region, obtaining a first time-density curve to obtain the maximum slope of the first time-density curve; For the at least one second region, obtaining a second time-density curve to obtain the maximum enhancement value of the second time-density curve; And Determining the myocardial blood flow according to the maximum slope and the maximum enhancement value.

2. The method according to claim 1, wherein The maximum slope is determined by the following method: For a plurality of first sub-segments of the first time-density curve, calculating a first slope of each first sub-segment; and Determining the maximum slope calculated among the plurality of first sub-segments as the maximum slope, wherein the plurality of first sub-segments are formed by connecting lines between every two adjacent first monitoring CT values of the plurality of first monitoring CT values of the at least one first region during the angiography process.

3. The method according to claim 1, wherein, The maximum enhancement value is determined by the following method: Calculating the difference between the maximum value and the minimum value among the plurality of second monitoring CT values of the at least one second region during the angiography process as the maximum enhancement value.

4. The method according to claim 1, wherein Determining the myocardial blood flow according to the maximum slope and the maximum enhancement value includes: Calculating the myocardial blood flow through a weighted linear combination of the maximum slope and the maximum enhancement value.

5. The method according to claim 1, wherein After obtaining the angiographic image including the coronary artery and the left ventricle adjacent to the coronary artery, it further includes: Preprocessing the angiographic image to obtain the preprocessed angiographic image; Segmenting the preprocessed angiographic image into the myocardial region of the left ventricle and the lumen region of the coronary artery; In the myocardial region of the left ventricle, extracting at least one first region of interest as the at least one first region; and In the lumen region of the coronary artery, extracting at least one second region of interest as the at least one second region.

6. The method according to claim 1, wherein: The first time-density curve is collected starting from a first trigger time, and the first trigger time is the time when the first monitoring CT value of the at least one first region first exceeds a preset first trigger value; And The second time-density curve is collected starting from a second trigger time, and the second trigger time is the time when the second monitoring CT value of the at least one second region first exceeds a preset second trigger value.

7. The method according to claim 6, wherein: The first time-density curve stops being collected at a first cut-off time, and the first cut-off time is configured to be the time when the first monitoring CT value of the at least one first region first exceeds a preset first threshold; The second time density curve stops collecting at a second cut-off time, which is configured as the time when the second monitored CT value of the at least one second region first exceeds a preset second threshold.

8. An apparatus for simulating myocardial blood flow, the apparatus comprising: A first unit configured to obtain an angiographic image including a coronary artery and a left ventricle adjacent to the coronary artery, the angiographic image including at least one first region and at least one second region, wherein the at least one first region is located in the myocardial region of the left ventricle and the at least one second region is located in the lumen region of the coronary artery; A second unit configured to obtain a first time density curve for the at least one first region to obtain a maximum slope of the first time density curve; A third unit configured to obtain a second time density curve for the at least one second region to obtain a maximum enhancement value of the second time density curve; And A fourth unit configured to determine the myocardial blood flow based on the maximum slope and the maximum enhancement value.

9. An electronic device, comprising: At least one processor; And At least one memory communicatively connected to the at least one processor; Wherein The at least one memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1-8.

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