Print Email Facebook Twitter Automatic Labeling of X-Ray Images Based on Deep Learning Title Automatic Labeling of X-Ray Images Based on Deep Learning Author Yin, Yunchao (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Intelligent Systems) Contributor Vilanova Bartroli, Anna (mentor) Van Pelt, Roy (mentor) Oliván Bescós, Javier (mentor) Degree granting institution Delft University of Technology Programme Computer Science Date 2018-09-24 Abstract Coronary artery disease is the most common type of heart disease, which influences 110 million people's health and causes 8.9 million deaths in 2015. Physicians can visualize the lesion in coronary arteries by cardiac angiography (X-ray image) during diagnosis and treatment of coronary artery disease. The pathological findings in cardiac angiography are reported per segment or per artery of the coronary artery tree, therefore, it requires to annotate the name of each segment or artery in the coronary artery tree. This thesis proposes a data-driven method as a first attempt at annotating cardiac angiography based on deep learning. The method aims at automatically regressing segment points between different segments on the coronary artery tree as the annotation of the cardiac angiography. The proposed data-driven cardiac angiography annotation methods can learn and generalize from manually annotated cardiac angiography examples, but its performance is limited by the number and quality of examples for learning. Subject Cardiac angiography annotationDeep Learning To reference this document use: http://resolver.tudelft.nl/uuid:8549a58e-a542-4504-aa55-f642004373b9 Embargo date 2020-09-17 Part of collection Student theses Document type master thesis Rights © 2018 Yunchao Yin Files PDF Automatic_Labeling_of_X_R ... arning.pdf 20.96 MB Close viewer /islandora/object/uuid:8549a58e-a542-4504-aa55-f642004373b9/datastream/OBJ/view