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dc.contributor.authorWang, Tsaipeien_US
dc.date.accessioned2018-08-21T05:57:02Z-
dc.date.available2018-08-21T05:57:02Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn2161-0363en_US
dc.identifier.urihttp://hdl.handle.net/11536/146959-
dc.description.abstractThis paper describes an iterative data-driven algorithm for automatically labeling coronary vessel segments in MDCT images. Such techniques are useful for effective presentation and communication of findings on coronary vessel pathology by physicians and computer-assisted diagnosis systems. The experiments are done on the 18 sets of coronary vessel data in the Rotterdam Coronary Artery Algorithm Evaluation Framework that contain segment labeling by medical experts. The performance of our algorithm show both good accuracy and efficiency compared to previous works on this task.en_US
dc.language.isoen_USen_US
dc.subjectMDCTen_US
dc.subjectcoronary artery imagingen_US
dc.subjectvessel labelingen_US
dc.subjectvessel tree matchingen_US
dc.subjectcomputer-assisted diagnosisen_US
dc.titleITERATIVE DATA-DRIVEN CORONARY VESSEL LABELINGen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2017 IEEE 27TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSINGen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000425458700085en_US
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