Deep-learning based, automated segmentation of macular edema in optical coherence tomography

Biomedical Optics Express

Volumn 8, Issue 7, 2017, Pages 3440-3448

  Lee, Cecilia S ^a   Tyring, Ariel J ^a   Deruyter, Nicolaas P ^a   Wu, Yue ^a   Rokem, Ariel ^c   Lee, Aaron Y ^a,b,c  

^a UNIVERSITY OF WASHINGTON SCHOOL OF MEDICINE   (United States)

^b Puget Sound Veteran Affairs ^*  (United States)

^c UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOINFORMATICS; DEEP LEARNING; IMAGE SEGMENTATION; NEURAL NETWORKS; OPHTHALMOLOGY; TOMOGRAPHY;

AUTOMATED SEGMENTATION; BIOMEDICAL IMAGES; CLINICAL IMAGES; COMPUTER VISION ALGORITHMS; CONVOLUTIONAL NEURAL NETWORK; DICE COEFFICIENT; INTRA-RETINAL FLUIDS; SEGMENTED IMAGES;

OPTICAL TOMOGRAPHY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CORRELATION COEFFICIENT; HUMAN; IMAGE ANALYSIS; IMAGE SEGMENTATION; LEARNING ALGORITHM; MACULAR EDEMA; OPTICAL COHERENCE TOMOGRAPHY; RETINA DETACHMENT; TRAINING; VALIDATION PROCESS;

EID: 85023600747     PISSN: None     EISSN: 21567085     Source Type: Journal    
DOI: 10.1364/BOE.8.003440     Document Type: Article

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