Direct Quantification of Coronary Artery Stenosis Through Hierarchical Attentive Multi-View Learning

• Published in: IEEE transactions on medical imaging Vol. 39; no. 12; pp. 4322 - 4334
• Main Authors: Zhang, Dong, Yang, Guang, Zhao, Shu, Zhang, Yanping, Ghista, Dhanjoo, Zhang, Heye, Li, Shuo
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Angiography; Arteries; Cardiovascular disease; Clinical decision making; Coronary artery; Coronary artery disease; coronary artery stenosis; Coronary vessels; Correlation; Decision making; direct quantification; Embedding; Estimation; Feature extraction; Ground truth; Health services; Heart diseases; Image reconstruction; Image segmentation; intraoperative treatment; Learning; Lesions; Medical treatment; Morphology; multi-view learning; Reconstruction; Stenosis; Stents; Task analysis; Workflow; X-ray angiography

Quantification of coronary artery stenosis on X-ray angiography (XRA) images is of great importance during the intraoperative treatment of coronary artery disease. It serves to quantify the coronary artery stenosis by estimating the clinical morphological indices, which are essential in clinical dec...