Boundary Guidance Network For Blood Vessel Segmentation In Coronary Angiography

As the prevalence of coronary artery diseases continues to rise in recent years,the workload and difficulty to treat these diseases become enormous.Therefore,a computer-based diagnosis and treatment auxiliary system regarded as alleviation of the problem has attracted increasing practitioners’attention.However,since there are various types of medical images,large differences among those types,and realistic difficulty of extracting features from the images,computer-aided diagnosis and treatment are still underway.This research is dedicated to a deep learning network that can automatically segment coronary angiography images and distinguish segments from branches.whose results can be reliable reference for doctors and also can be used on vascular tree establishment to measure blood vessels diameters.The foremost thesis results are as follows:at the beginning,the thesis built a well-divided and well-labeled dataset with 12,900 images according to coronary angiography of 2384 patients;Second,we proposed a segmentation model based on a generative confrontation network,which initially realized automatic segmentation of blood vessel segments and branches.Based on basic segmentation network U-Net supplementing with residual-structured coding block,we proposed a boundary guidance network aiming to avoid negligence of stenosis vessel segmentation.The model applied the boundary guidance module and weight distribution module.Besides,the background noise interference is reduced with the application of bottom-hat computing;Last but not the least,the thesis promoted the accuracy of locating pixels in each vessel segment and solved the problem of intra-class pixel errors by introducing regional positioning module which also ceased the problem of inter-class pixel confusion to some extent.After including the boundary guidance module and weight distribution module,the Dice score of blood-vessel binary segmentation was raised up to 0.988 according to the results of experiments.Besides,promotion of Dice score was shown in all fifteen types of blood vessel segments with the importation of regional positioning module.