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Disease Generating Model for 3D Display of the Effect of Treatment on 3D Optical Coherence Tomography Images
Author(s) -
Nguyen Ngoc Anh Huyen,
Ai Yamakawa,
Dai Kodama,
Shinji Tsuruoka,
Hiroharu Kawanaka,
Haruhiko Takase,
Yukitaka Uji,
Hisashi Matsubara,
Fumio Okuyama
Publication year - 2013
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2013.09.160
Subject(s) - retinal , optical coherence tomography , computer science , retina , artificial intelligence , retinal pigment epithelium , computer vision , ophthalmology , medicine , optics , physics
In ophthalmology, the needs of retina diagnosis using optical coherence tomography (OCT) have been growing and the automatic measurement of a retinal thickness and its quantitative evaluation are desired for the diagnosis of retinal diseases. Previously, the automatic measurement methods of the retinal thickness have been reported for retinal OCT images. However, the methods extracted the retinal border lines intermittently for OCT images, but cannot measure the effect of treatment for an abnormal area automatically. And it's difficult in evaluating the effectiveness of laser treatment or medication.In this paper, we propose a disease generating model for three dimensional (3D) display of the effect of treatment. To extract the change of the abnormal area, we applied automatic measurement method of a retinal thickness in OCT image.The method employs a new dynamic contour model (“One Directional Active Net (ODAN)”) to extract two retinal border lines, and the thickness is defined from Inner Limiting Membrane (ILM) to Retinal Pigment Epithelium (RPE). We confirmed the usefulness of the ODAN by the experimental results for normal and retinal disease OCT images. The proposed method is useful as the visual evaluation for the effect of treatment for retinal disease

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