Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images

Journal of Biomedical Optics

Volumn 21, Issue 7, 2016, Pages

  Keller, Brenton ^a   Cunefare, David ^a   Grewal, Dilraj S ^b   Mahmoud, Tamer H ^b   Izatt, Joseph A ^a,b   Farsiu, Sina ^a,b  

^a Duke University   (United States)

^b DUKE UNIVERSITY EYE CENTER   (United States)

Author keywords

algorithm; graph search; image segmentation

Indexed keywords

ADAPTIVE OPTICS; ALGORITHMS; CARBON DIOXIDE ARC WELDING; DYNAMIC PROGRAMMING; GRADING; GRAPH THEORY; OPTICAL TOMOGRAPHY; TOMOGRAPHY;

ADAPTIVE SEGMENTATION; AUTOMATIC SEGMENTATIONS; DIJKSTRA'S SHORTEST PATH ALGORITHM; GRAPH SEARCH; ITS APPLICATIONS; MACULAR PATHOLOGY; RETINAL OPTICAL COHERENCE TOMOGRAPHY; SEGMENTATION TECHNIQUES;

IMAGE SEGMENTATION;

ALGORITHM; DIAGNOSTIC IMAGING; HUMAN; MACULAR DEGENERATION; OPTICAL COHERENCE TOMOGRAPHY;

ALGORITHMS; HUMANS; MACULAR DEGENERATION; TOMOGRAPHY, OPTICAL COHERENCE;

EID: 84980018868     PISSN: 10833668     EISSN: 15602281     Source Type: Journal    
DOI: 10.1117/1.JBO.21.7.076015     Document Type: Article

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