Machine learning based vesselness measurement for coronary artery segmentation in cardiac CT volumes

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7962, Issue , 2011, Pages

  Zheng, Yefeng ^a   Loziczonek, Maciej ^a   Georgescu, Bogdan ^a   Zhou, S Kevin ^a   Vega Higuera, Fernando ^b   Comaniciu, Dorin ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

^b Siemens Healthcare ^*  (Germany)

Author keywords

Coronary centerline extraction; coronary lumen segmentation; machine learning; vesselness measurement

Indexed keywords

CARDIAC CT; CENTERLINE EXTRACTION; CORONARY ARTERY DISEASE; CORONARY ARTERY SEGMENTATION; CORONARY LUMEN; DATA SETS; DEVELOPED COUNTRIES; DOMAIN-SPECIFIC KNOWLEDGE; END POINTS; HEART SURFACE; IMAGE CONTEXT INFORMATION; IMAGE FEATURES; LUMEN SEGMENTATIONS; MACHINE LEARNING; PRE-PROCESSING STEP; SHORTEST PATH; SHORTEST PATH COMPUTATIONS; SPEED-UPS; VESSEL LUMEN; VESSELNESS MEASUREMENT;

COMPUTERIZED TOMOGRAPHY; DIAGNOSIS; DISEASES; GRAPH THEORY; IMAGE PROCESSING; IMAGING SYSTEMS; LEARNING SYSTEMS; MEDICAL IMAGING;

HEART;

EID: 79957990394     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.877233     Document Type: Conference Paper

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