Pathology hinting as the combination of automatic segmentation with a statistical shape model

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

Volumn 7512 LNCS, Issue , 2012, Pages 599-606

  Dufour, Pascal A ^a,b   Abdillahi, Hannan ^c   Ceklic, Lala ^c   Wolf Schnurrbusch, Ute ^b,c   Kowal, Jens ^a,b  

^a UNIVERSITY OF BERN   (Switzerland)

^b UNIVERSITY OF BERN   (Switzerland)

^c Bern Photographic Reading Center   (Switzerland)

Author keywords

Multi surface segmentation; Optical coherence tomography; Pathology hinting; Statistical shape model

Indexed keywords

ALDEHYDES; IMAGE ENHANCEMENT; MEDICAL COMPUTING; MEDICAL IMAGING; OPHTHALMOLOGY; OPTICAL TOMOGRAPHY; PATHOLOGY; PETROLEUM RESERVOIR EVALUATION; POPULATION STATISTICS; TOMOGRAPHY;

AGE-RELATED MACULAR DEGENERATION; AUTOMATIC SEGMENTATIONS; HEALTHY POPULATION; MULTI-SURFACE; RETINAL PIGMENT EPITHELIUM; SEGMENTATION ALGORITHMS; SEGMENTATION TECHNIQUES; STATISTICAL SHAPE MODEL;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; OPTIC DISK ANOMALY; OPTICAL COHERENCE TOMOGRAPHY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, BIOLOGICAL; MODELS, STATISTICAL; OPTIC DISK DRUSEN; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, OPTICAL COHERENCE;

MLCS; MLOWN;

EID: 84872934455     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33454-2_74     Document Type: Conference Paper

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