Conference proceeding
Segmentation of the surfaces of the retinal layer from OCT images
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, Vol.9(Pt 1), pp.800-807
2006
DOI: 10.1007/11866565_98
PMID: 17354964
Abstract
We have developed a method for the automated segmentation of the internal limiting membrane and the pigment epithelium in 3-D OCT retinal images. Each surface was found as a minimum s-t cut from a geometric graph constructed from edge/regional information and a priori-determined surface constraints. Our approach was tested on 18 3-D data sets (9 from patients with normal optic discs and 9 from patients with papilledema) obtained using a Stratus OCT-3 scanner. Qualitative analysis of surface detection correctness indicates that our method consistently found the correct surfaces and outperformed the proprietary algorithm used in the Stratus OCT-3 scanner. For example, for the internal limiting membrane, 4% of the 2-D scans had minor failures with no major failures using our approach, but 19% of the 2-D scans using the Stratus OCT-3 scanner had minor or complete failures.
Details
- Title: Subtitle
- Segmentation of the surfaces of the retinal layer from OCT images
- Creators
- Mona Haeker - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA. mona-haeker@uiowa.eduMichael AbràmoffRandy KardonMilan Sonka
- Resource Type
- Conference proceeding
- Publication Details
- Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, Vol.9(Pt 1), pp.800-807
- DOI
- 10.1007/11866565_98
- PMID
- 17354964
- Publisher
- Germany
- Language
- English
- Date published
- 2006
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9983980392002771
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