Intra-retinal layer segmentation in optical coherence tomography using an active contour approach

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5762 LNCS, Issue PART 2, 2009, Pages 649-656

  Yazdanpanah, Azadeh ^a   Hamarneh, Ghassan ^a   Smith, Benjamin ^a   Sarunic, Marinko ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE CONTOURS; AUTOMATIC SEGMENTATIONS; CIRCULAR SHAPE; DEPTH RESOLVED IMAGING; DIAGNOSTIC TECHNIQUES; ENERGY FUNCTIONALS; GANGLION CELLS; LEAST SQUARE; LOW CONTRAST; NON-INVASIVE; OPTICAL COHERENCE TOMOGRAPHY; RETINAL DEGENERATIONS; RETINAL LAYERS; RODENT MODELS; SEGMENTATION RESULTS; SHAPE PARAMETERS; SIMILARITY COEFFICIENTS; SYNTHETIC EXPERIMENTS;

COHERENT LIGHT; IMAGE SEGMENTATION; MEDICAL COMPUTING; OPHTHALMOLOGY; TOMOGRAPHY;

EDGE DETECTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; CYTOLOGY; HUMAN; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; NERVE CELL NETWORK; REPRODUCIBILITY; RETINA NERVE CELL; RETINOSCOPY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; NERVE NET; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; RETINAL NEURONS; RETINOSCOPY; SENSITIVITY AND SPECIFICITY;

EID: 79551681631     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_79     Document Type: Conference Paper

References (10)

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