92 results about "Coronary angiography" patented technology

The invention discloses a coronary angiography image blood vessel segmentation system based on multi-scale feature fusion. According to the invention, through the innovative design of the adaptive morphological sensing module, the system can dynamically analyze the anatomical structure characteristics of the blood vessel: the differentiable morphological operation layer converts the corrosion expansion operation into a learnable feature extraction process, so that the network can autonomously identify the gradient change and boundary trend of the blood vessel wall; the dynamic nuclear adaptation mechanism adjusts the scale and direction of morphological operation in real time according to the local blood vessel diameter and curvature characteristics, interference of surrounding tissues in a main blood vessel area can be inhibited, and continuous expression can be enhanced for capillary branches. Through deep fusion of dissection driving and data driving, the topological structure integrity of a segmentation result at a blood vessel bifurcation point and a narrow lesion area is remarkably improved, and the common problems of blood vessel fracture and misconnection in a traditional method are effectively avoided.

The invention provides a DSA-oriented X-ray coronary angiography image blood vessel segmentation method and system, and relates to the technical field of image processing and deep learning. The method comprises the following steps: firstly, acquiring a target segmentation image and a reference image based on X-ray coronary artery angiography video data, and forming a training sample by the reference image and the target segmentation image to construct a training data set; then constructing a segmentation network model; the segmentation network model comprises a main encoder, an auxiliary encoder, a plurality of up-sampling attention modules, a similarity attention module and a decoder; calculating a total loss function by using the segmentation mask of the target segmentation image, and optimizing the segmentation network model; and finally, inputting an X-ray coronary artery angiography image data set needing to be segmented into the trained segmentation network model to obtain a segmentation result. According to the method, an X-ray perspective image before radiography is compared with a target segmentation image, so that a neural network is helped to distinguish a foreground from a background, and blood vessels are accurately recognized.

A method for coronary road mapping may include receiving a current image associated with a medical scan, determining an image that matches the current image from a sequence of images for which respective blood vessel maps have been determined, and overlaying the current image with the blood vessel map associated with the matching image. The sequence of images may be captured when a contrast agent was present, and the matching image may be identified in response to determining that the physiological phase (e.g., cardiac cycle) and / or view depicted by the image match those depicted by the current image. Motion compensation may be performed as part of the blood vessel overlay, which may enable better visualization of blood vessels and medical device(s) (e.g., a catheter) placed in the blood vessels even when the contrast agent is worn out.

The invention provides a construction method of a coronary heart disease risk prediction model based on deep learning, and the method comprises the following steps: S1, obtaining examination data of patients recorded in a hospital, and respectively obtaining 12-lead electrocardiogram data of a coronary heart disease patient and a non-coronary heart disease patient in an HL7 format according to a coronary angiography examination result; s2, preprocessing the acquired electrocardiogram data; s3, dividing the preprocessed electrocardiogram data into a training set, a verification set and a test set; constructing a ResNet-LSTM integrated model, inputting features extracted by the ResNet neural network into LSTM for classification, and inputting electrocardiogram data into the model for training and verification by adopting ten-fold cross validation to obtain a trained model and a verification result; s4, optimizing parameters of the trained model based on a verification result; and S5, performing coronary heart disease risk prediction on the optimized integrated model by using test set data. The space and time information of the electrocardiogram can be fully captured, and more accurate coronary heart disease risk prediction is realized.

The invention discloses a hemostasis device for a radial artery puncture part after coronary angiography. The hemostasis device comprises a fixing assembly, a fixing sleeve, a rotating ring and a pressing head. The fixing sleeve is arranged outside the fixing assembly in a sleeving mode, the fixing sleeve and the fixing assembly are connected through the large spring, the lower end of the fixing assembly is movably connected with the rotating ring, the pressing head is arranged in the rotating ring in a sleeving mode, and the pressing head is arranged in the fixing assembly in a sleeving mode. The pressing head can be detachably fixed through the arranged fixing assembly, one-key fixing can be achieved only by directly pulling the fixing sleeve in the fixing process, fixing is rapid and convenient, meanwhile, the fixing head is made into a detachable form, the pressing head can be installed in the using process, the pressing head can be replaced due to the detachable installation arrangement, and the pressing head is convenient to use. The risk caused by cross infection can be effectively reduced, and meanwhile materials can be saved to a great extent.

The invention discloses a femoral artery compression hemostasis device after coronary angiography, through the combined design of an adjusting bandage and a neck bandage, the device can adapt to patients with different body types, the neck bandage assists in fixing and pulling the device, and the problem that a traditional compression hemostasis device is unstable in fixation due to body type difference is effectively solved. The compression assembly of the device is designed to be capable of being adjusted in a sliding mode, the hemostasis block can be accurately moved to the puncture point position, and it is ensured that compression force directly acts on a target area. Meanwhile, the angle of the compression assembly is adjusted through the height difference of the friction bolt, and the requirements for different puncture angles are further met. According to the device, by means of the design that the drawing grooves are formed in the two sides of the fixing frame, the hemostatic cotton can be conveniently arranged in the drawing grooves in a sliding mode, no matter how the compression angle changes, the hemostatic cotton can be in full contact with a puncture point all the time, and therefore the uniform and stable compression hemostasis effect is achieved.

The invention provides a coronary angiography tree structure, a central line path extraction method, a central line path extraction device, equipment and a medium. The method comprises the following steps: acquiring a coronary angiography image; the coronary angiography image is input to a feature extraction module based on a Vision Transform architecture, and the feature extraction module is used for extracting the coronary angiography image; a feature extraction module based on a Vision Transform architecture is used for extracting multi-scale features; inputting the multi-scale features into an image segmentation decoder and a key point extraction decoder to generate a blood vessel segmentation result and key point coordinates; wherein the key point coordinates comprise a starting point coordinate and an end point coordinate on the path; fusing the key point coordinates, the blood vessel segmentation result and the coronary angiography image to serve as target input information; a center line path is extracted according to the target input information on the basis of a path generation algorithm of Vision Transform; and fusing the center line paths to form a coronary artery tree structure and a path map thereof.

The invention relates to the technical field of medical auxiliary instruments, in particular to a self-adaptive compression hemostasis device used after coronary angiography and a hemostasis method.The self-adaptive compression hemostasis device comprises an annular belt used for being worn, a pressure sensor, a humidity sensor, an air pump and a control panel, the pressure sensor and the humidity sensor are arranged on a detection part, and the inner side of the annular belt is provided with a pressure area used for covering a puncture position; an air bag is arranged in the pressure area, a detection part used for making contact with the puncture position is arranged on the inner side of the air bag, a catheter used for conveying air is arranged on the air bag, and the pressure area is constructed to apply compression force to the puncture position through air inflation of the air bag; the air pump is configured to achieve inflation pressurization and exhaust pressure reduction of the air bag by switching the current direction. The control panel is configured to use the control module to drive the air pump to adjust the state of the air bag by taking a preset hemostasis and safety threshold value as a reference so as to form continuous and dynamic self-adaptive adjustment on the compression force of the puncture part, and form negative feedback control on the self-adaptive adjustment by receiving the first electric signal and the second electric signal.

The application discloses a coronary angiography image segmentation method and system based on semantic guidance, and belongs to the field of medical image processing. In view of the problems of semantic inconsistency, easy breaking of blood vessels and easy loss of small branches in multi-scale feature fusion of existing methods, the method of the application extracts multi-scale local structure features through a main encoder, and simultaneously extracts multi-scale original global semantic features by using an image encoder of a pre-trained medical visual basic model; after aligning the multi-scale original global semantic features, the multi-scale original global semantic features are spliced, semantic bases are constructed by performing gate fusion in a unified semantic space; multi-scale semantic reconstruction features matched with each layer of a decoder are generated and decoded by the semantic bases, and the multi-scale semantic reconstruction features are injected into the decoder layer by layer, and the multi-scale local structure features of the encoder are connected by jump connection, so that the features are guided to recover. The application realizes cross-scale semantic consistency modeling, effectively improves the blood vessel connectivity and small branch reservation capability, and is suitable for coronary angiography image segmentation.

The embodiment of the present application discloses a method and computer device for determining blood vessel flow velocity. The method includes: acquiring angiography sequence images, finding a coronary angiography image that meets the best development conditions in the angiography sequence images as the best coronary angiography image, selecting the coronary angiography image arranged before the timestamp of the best coronary angiography image in the angiography sequence images in sequence as the target coronary angiography image, the target coronary angiography image and the best coronary angiography image forming an image segmentation set, generating a blood vessel length change graph based on the image segmentation set, determining the conduction start time and the conduction end time based on the blood vessel length change graph, and determining the blood vessel flow velocity based on the main branch vessel length, the conduction start time and the conduction end time. The embodiment of the present application does not need to analyze all coronary angiography images, and selects the best coronary angiography image and the target coronary angiography image arranged before the best coronary angiography image for analysis, which can reduce the number of blood vessel segmentations.

This application provides a method, device, equipment, and storage medium for matching vascular centerlines, comprising: acquiring a first vascular centerline in a first coronary angiography image and a second vascular centerline in a second coronary angiography image; for each first vascular center point, determining an initial point pair matching anomaly based on the intersection of the polar line corresponding to the first vascular center point and the second vascular centerline; and determining the second vascular center point to be matched with the first vascular center point based on the intersection of the polar line corresponding to the first vascular center point and the second vascular centerline, and the second vascular center points already matched with the previous first vascular center point. In this way, it is possible to accurately determine an anomaly in the point pair matching of a certain point on the vascular centerline based on the intersection of the polar lines, and to correct the matching relationship based on the intersection and other determined point pairs, thereby re-determining the matching point of the vascular center point.

The invention discloses a contrast agent filtering device for coronary surgery and a using method thereof, the device is integrally in a plastic bag shape and comprises a filtering bag body, the bottom of the filtering bag body is provided with a transfusion connector and a blood transfusion connector which are provided with sealing covers, and an inner opening is sleeved with a filter screen support with a filter screen; the filter bag body is divided into a filter area and an adsorption particle storage area through a middle seal, a flushing connector and a hanging hole are arranged at the top, and the filter bag body can be matched with a vibration disc for use. The use method comprises the steps that blood containing a contrast agent is extracted and input into the filtering area, the middle seal is opened through pressing, the blood makes full contact with the adsorption particles through vibration or manual extrusion so as to adsorb the contrast agent, then the filtered blood is infused back, and residual plasma can be infused back after being diluted with normal saline. The device is simple in structure, low in cost and easy and convenient to operate, the filtering effect is improved by 30% compared with the prior art, the adsorption rate reaches 75%-85%, contrast agents in blood can be effectively removed, damage to the kidney of a patient is reduced, and the device is particularly suitable for blood treatment of the patient after coronary angiography.

The auxiliary fixing device comprises a supporting frame, a two-way threaded rod is rotationally installed on the inner wall of the supporting frame, guide rods are arranged at the two ends of the two-way threaded rod, and the guide rods are fixedly installed on the inner wall of the supporting frame; the two-way threaded rod rotationally penetrates through the supporting frame and is fixedly connected with an output shaft of a motor, the motor is fixedly installed on the surface of the supporting frame, the outer sides of the two ends of the two-way threaded rod are sleeved with adjusting blocks in a threaded mode correspondingly, the adjusting blocks slidably sleeve the outer sides of the guide rods correspondingly, and sliding grooves are formed in the two sides of the supporting frame correspondingly; one end of the adjusting block is fixedly connected with the fixing bandage, the other end of the adjusting block is fixedly connected with the locking assembly through the connecting plate, and the locking assembly is used for fixing the fixing bandage. The problems that in the prior art, fixation is not firm, adjustment cannot be achieved, comfort is poor, and observation is inconvenient are solved.

The invention discloses a heart multi-modal image feature extraction method and device, equipment, a medium and a product, and relates to the technical field of medical image processing, and the method comprises the steps: obtaining multi-modal heart image data, patient information and case information in a multi-center imaging department and an ultrasound department; labeling the multi-modal heart image data, and constructing a multi-modal iconography feature database; establishing a database platform comprising a server storage control terminal and a data screening and uploading terminal; opening a communication link after verifying the identity of the requester; training is carried out based on the marked multi-mode heart data and a deep learning algorithm so as to obtain heart structure features of heart ultrasound and nuclear magnetic images through coronary angiography (CCTA) image data; finally, the system is deployed and applied clinically. According to the method, the heart structure features of the other two modal images are predicted based on the single-modal CCTA image data, the diagnosis range based on the CCTA image data is expanded, the medical overhead is saved, and the diagnosis and treatment efficiency and accuracy are improved.

The application discloses a coronary angiography blood vessel tracking method and system based on a template matching method, belongs to the technical field of blood vessel image processing, and comprises the following steps: acquiring any adjacent frame angiography image in an angiography sequence, acquiring a sample point sequence, and marking a to-be-reasoned point; judging whether an abnormal point exists in a tracking process or not, marking the abnormal point as a to-be-corrected point; correcting a tracking result of a next frame based on a position of the to-be-corrected point in the Nth frame; reasoning the to-be-reasoned point to obtain a tracked result after reasoning; performing similarity comparison on the position of the tracked sample point in the N+1th frame and the position of the tracked sample point in the Nth frame, if the positions are not similar, then exchanging the tracking result of the sample point, and iterating all sample points according to the process until all sample points are rearranged to obtain a final tracking result. The application solves the problem that the existing technology cannot realize accurate matching of the sample point by simply relying on the template matching, and the problems of missing tracking points, inaccurate positions and disorder of the final sample sequence order.

The present invention discloses an automatic segmentation method for coronary angiography images based on SFAG-DeepLabv3+. The method is based on the DeepLabv3+ backbone network and proposes the AG-DeepLabv3+ network. In the encoder part, an Adaptive Hybrid Dilated Convolution Double Pooling (ADP) module is proposed based on the ASPP module to construct a strengthened feature extraction network. A Gaussian Context Space (GCS) module is introduced between the encoder and the decoder. By adaptively reorganizing features in the channel dimension and the spatial dimension, the information loss caused during the compression and decompression process of information from the encoder to the decoder is reduced, and the problem of blood vessel breakage during blood vessel segmentation by the model due to information loss during the compression and decompression process of information from the encoder to the decoder is solved. In the decoder part, bicubic interpolation upsampling is adopted, and by utilizing more adjacent pixel information, the continuity of blood vessel segmentation is improved.

The invention relates to the technical field of medical apparatus and instruments, in particular to multifunctional forearm hematoma compression equipment for cardiology department patients after coronary angiography, which comprises a base, a first supporting seat, a second supporting seat and the like, and the base is provided with the first supporting seat and the second supporting seat which are respectively used for supporting a forearm and an upper arm; the first supporting base and the second supporting base are each provided with an arc-shaped bearing plate with the concave middle, the ends of the bearing plates are each provided with an elastic fixing band, and the ends of the fixing bands are detachably connected with the bearing plates through buckles. The forearm of a patient is pressed by arranging the height-adjustable sleeve with the elastic piece, the effect of conveniently adjusting the pressing force and improving the experience of the patient is achieved, meanwhile, by arranging the buckle structure at the end of the fixing band, the fixing band can be conveniently tightened and loosened, then an ice bag can be conveniently used for cold compress, and the use effect is good. The forearm pressure of the patient is reduced, and hematoma enlargement is avoided.

The present application relates to a kind of DSA coronary vessel segmentation deep learning method of edge and topological feature, comprising the following steps: obtaining DSA coronary angiography image dataset and corresponding coronary vessel label dataset;Data is input into deep learning network, the deep learning network is end-to-end U type deep learning network, include improved bidirectional Transformer module and multi-scale semantic fusion module, and encoder and decoder are connected by jump connection and multi-scale semantic fusion module;Coronary vessel segmentation model is trained in three stages using the composite loss function comprising Dice loss, Focal loss, edge loss and topological loss, the segmentation model of the training completion can be carried out complete segmentation to the coronary vessel in DSA coronary angiography picture;Using composite evaluation index, the overall segmentation accuracy of segmentation model, edge segmentation accuracy and the ability of keeping topological consistency are comprehensively evaluated.

A technical solution disclosed in the present invention provides a segmented calculation system for coronary blood flow reserve, and another technical solution of the present invention provides a segmented calculation method for coronary blood flow reserve. The segmented calculation system and method for coronary blood flow reserve provided by the present invention only require the import of coronary angiography images at rest and maximum hyperemia, and can measure the coronary blood flow reserve CFR without the use of a guidewire and a temperature sensor, so there is no need to inject room temperature saline into the patient's coronary artery multiple times. On the one hand, the present invention reduces the trauma suffered by the patient, reduces the difficulty of surgical operation, greatly shortens the operation time, and saves surgical costs. On the other hand, the present invention can not only output the average blood flow reserve value of the coronary artery, but also output the local blood flow reserve values ​​corresponding to the proximal, middle and distal segments of the coronary artery. The measurement results are more comprehensive, reducing the influence of each branch on the average blood flow reserve value.

The invention discloses a disposable coronary angiography catheter, and relates to the field of coronary angiography, the disposable coronary angiography catheter comprises a rectangular soft magnetic base, the top of the rectangular soft magnetic base is fixedly provided with a fixing plate, the top of the fixing plate is provided with a rapid replacement assembly, the rapid replacement assembly comprises a first cylinder, and the first cylinder is fixedly installed on the side wall of the fixing plate; a plurality of circular holes are formed in the first cylinder in an annular array mode, a ball body is slidably connected into each circular hole, and the situation that second coronary angiography catheters of different models need to be positioned again when replaced can be avoided through the arrangement of the quick replacement assembly, so that the traditional time for replacing the coronary angiography catheters is greatly shortened, and the replacement efficiency of the coronary angiography catheters is improved. The surgical risk of a patient is reduced, meanwhile, switching of multiple catheters is achieved through a single puncture point, the number of times of vascular puncture is reduced, the surgical risk of the patient is further reduced, meanwhile, the surgical requirements of second coronary angiography catheters of different models can be met, and therefore the adaptability of the device is improved.

An embodiment of the present invention relates to a method and apparatus for quantitative analysis of coronary angiography based on angiography videos. The method includes: obtaining an angiography video; extracting video frame images to generate a first image sequence; performing target detection and semantic segmentation processing on each first image in the first image sequence for the stenotic segment vessels, so as to obtain one or more target detection frames for marking the stenotic segment vessels and a stenotic segment vessel mask image within each target detection frame on each first image; performing image optimization processing on the first image sequence to obtain a specified number of optimized images; performing quantitative analysis of coronary angiography on the stenotic segment vessel mask images within each target detection frame on each optimized image to generate corresponding vessel stenosis rates. Through the present invention, the excessive dependence on manual experience in traditional practices can be eliminated, and the accuracy of image extraction and the calculation accuracy of stenosis rates can be improved.

The present invention relates to the field of model construction technology, and in particular to a method and system for constructing a risk assessment model for myocardial infarction patients. The method comprises the following steps: collecting vital sign data and coronary angiography images of myocardial infarction patients through a medical information system, and performing electrocardiogram signal-vascular motion mapping processing based on the coronary angiography images of myocardial infarction patients, while simultaneously performing blocked electrocardiogram signal pre-gradient feedback identification to obtain blocked electrocardiogram pre-gradient feedback data; performing electrocardiogram signal phase offset analysis on the blocked electrocardiogram pre-gradient feedback data, and constructing a risk assessment model for myocardial infarction patients to obtain a risk assessment model for myocardial infarction patients; and performing automated monitoring firmware design on the risk assessment model for myocardial infarction patients to obtain monitoring firmware for the risk assessment model for myocardial infarction patients. The present invention makes the assessment model construction technology more perfect by optimizing the construction technology of the risk assessment model for myocardial infarction patients.

The application discloses a scale perception progressive learning method for X-ray coronary angiography stenosis segmentation. The technical problem to be solved is how to solve the problem of insufficient segmentation accuracy caused by multi-scale characteristics and small target characteristics in coronary angiography stenosis segmentation. The application combines a scale perception strategy and a progressive feature reservation mechanism to provide a scale perception progressive learning method for X-ray coronary angiography stenosis segmentation. The application significantly improves the segmentation capability of multi-scale stenosis. The scale perception strategy dynamically aggregates context features of different scales, effectively adapts to the scale difference of coronary arteries in XCA images, enhances the sensitivity of the model to subtle stenosis changes, realizes more accurate stenosis boundary delineation, effectively solves the problem of easy loss of small target information, improves the robustness of the model to complex background interference, has stronger generalization capability, can adapt to different devices and imaging conditions, reduces the work burden of doctors and improves efficiency.

The invention discloses a lipid T-LCBI quantification method and system based on multi-modal space fusion, and the method comprises the steps: obtaining multi-modal blood vessel imaging data for registration, and achieving image distortion correction through cross-correlation correction; quantizing the boundary of the lipid plaque based on the fusion data, and obtaining quantized lipid plaque volume data based on continuous multi-frame fusion data; constructing blood vessel body data based on continuous multi-frame fusion data, fusing the blood vessel body data with coronary angiography data, and calculating a lipid plaque space correction coefficient of the curved blood vessel segment based on blood vessel space trend information; calculating a lipid volume based on the quantized lipid plaque data and a spatial correction coefficient; and calculating the T-LCBI index according to the ratio of the lipid volume to the total volume. Through registration fusion and distortion correction of multi-modal imaging data, a lipid boundary quantification bottleneck is broken through, blood vessel body data and coronary angiography data are fused, complete space trend information is constructed, and the calculation accuracy of an LCBI index is improved.

The present invention belongs to the technical field of target tracking, and discloses an automatic tracking method, device, equipment and storage medium for coronary angiography marker points. The method includes: obtaining a target coronary angiography video, and obtaining a marker frame image from the target coronary angiography video; determining target implicit information according to the position coordinates of the marker frame image; inputting the target implicit information and the marker frame image into a trained tracking model to obtain the predicted position coordinates of the marker points in the marker frame image and output layer information; determining whether the marker frame image is the last frame image in the target coronary angiography video; if not, using the next frame image of the marker frame image as a new marker frame image, and using the output layer information as new target implicit information to obtain the predicted position coordinates of the new marker frame image until the marker frame image is the last frame image in the target coronary angiography video. It can realize the tracking of the marker points in the target coronary angiography video.

A radial artery hemostasis device used after coronary angiography comprises a shell and a threaded rod, the inner wall of the shell is in threaded connection with the threaded rod, a radial artery hemostasis double-fixing structure is arranged on the right side of the outer wall of the shell, the lower end of the threaded rod is rotationally connected with a block through a bearing, and two sliding rods are fixedly connected to the upper end of the outer wall of the block. The outer wall of the sliding rod is in sliding connection with the shell. According to the radial artery hemostasis device used after coronary angiography, through cooperation of a radial artery hemostasis double-fixing structure and a hook-and-loop fastener, the vertical rod is pushed to abut against the ratchet wheel, a tree crown is pulled upwards to be separated from the ratchet wheel, meanwhile, the vertical rod can apply pressure to the spring, and after the arm of a patient is wound and fixed through the bandage, the arm is fixed through the hook-and-loop fastener. The bandage and the wrist of a patient can be doubly fixed through the hanging ring hooks and the hook-and-loop fasteners at the end and the tail end of the bandage, the problem that in the prior art, the bandage is fixed only through the hook-and-loop fasteners, and bleeding is caused by accidental loosening or falling off is solved, and then stability and completeness are effectively improved.

The application provides a bridge vessel segmentation and extraction method, device, system and readable storage medium, wherein position information of an inlet and position information of an outlet of a bridge vessel are acquired based on coronary angiography image data, and a segmentation result of the bridge vessel is acquired; then the segmentation result is screened by using the position information of the inlet and the position information of the outlet of the bridge vessel, so that the bridge vessel is extracted. The application screens the segmentation result by using the position information of the inlet and the position information of the outlet of the bridge vessel, optimizes the segmentation result, improves the accuracy of the extracted bridge vessel, and further improves the accuracy of the prognosis evaluation of the bridge vessel. Moreover, the application can be automatically completed without interaction with a user, and has higher segmentation efficiency and consistency.

The application relates to the technical field of electric field ablation, and particularly discloses an electric field ablation method and an ablation catheter for atherosclerotic plaque, which comprises the following steps: analyzing the lesion degree of a target stenosis site during coronary angiography, and judging whether the target animal needs to be focused on according to the distribution of all stenosis sites and the lesion degree of the stenosis sites; through the analysis of the lesion degree of the target stenosis site, the application is helpful for doctors to accurately diagnose the illness of patients, and is helpful for doctors to understand the severity of the lesion, so that a targeted treatment plan can be made; the analysis of the lesion degree of the stenosis site is also helpful for predicting the illness progress and prognosis of the patients; meanwhile, during the treatment process, the change of the lesion degree of the stenosis site is regularly evaluated, so that the treatment effect can be known; through the judgment of whether the target animal needs to be focused on, the animals with serious illness can be focused on, and the animals needing to be focused on are gathered, so that the resources can be most effectively utilized.

The invention relates to the technical field of medical diagnosis, in particular to a gray region diagnosis accuracy improving method and system based on angiography fractional flow reserve, and the method comprises the steps: obtaining an initial image through coronary artery angiography equipment, extracting blood vessel and blood flow combined features through a multi-modal feature fusion network, and obtaining a blood vessel and blood flow combined feature; and carrying out gray region identification, lesion positioning and quantitative analysis by combining a gray region classifier and a deep learning model, and finally generating a diagnosis report. According to the method, the gray region data characterization capability and diagnosis accuracy can be remarkably improved, and the clinical high-precision requirement is met.

The present application provides a cardiac cycle detection method and apparatus, electronic device, and storage medium, comprising: segmenting each image in a coronary angiography image sequence to obtain a segmentation result; constructing an image description feature corresponding to each image in the image sequence based on multiple segmentation results corresponding to the image sequence; constructing a feature similarity sequence based on the multiple image description features corresponding to the image sequence; and determining the corresponding phase of the cardiac cycle for each image in the image sequence based on the feature similarity sequence and the multiple segmentation results corresponding to the image sequence. The present application scheme detects the cardiac cycle based on images generated by coronary angiography.