Conference proceeding
Geodesic Graph Cut Based Retinal Fluid Segmentation in Optical Coherence Tomography
Proceedings of the Ophthalmic Medical Image Analysis Second International Workshop, OMIA 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 9, 2015, pp.49-56
Munich, Germany
10/2015
DOI: 10.17077/omia.1026
Abstract
Age-related macular degeneration (AMD) is a leading cause of blindness in developed countries. Its most damaging form is characterized by accumulation of fluid inside the retina, whose quantification is of utmost importance for evaluating the disease progression. In this paper we propose an automated method for retinal fluid segmentation from 3D images acquired with optical coherence tomography (OCT). It combines a machine learning approach with an effective segmentation framework based on geodesic graph cut. After an image preprocessing step, an artificial neural network is trained based on textural features to assign to each voxel a probability of belonging to a fluid. The obtained probability maps are used to compute minimal geodesic distances from a set of identified seed points to the remaining unassigned voxels. Finally, the segmentation is solved optimally and efficiently using graph cut optimization. The method is evaluated on a clinical longitudinal dataset consisting of 30 OCT scans from 10 patients taken at 3 different stages of treatment. Manual annotations from two retinal specialists were taken as the gold standard. The segmentation method achieved mean precision of 0.88 and recall of 0.83, with the combined F1 score of 0.85. The segmented fluid volumes were within the measured inter-observer variability. The results demonstrate that the proposed method is a promising step towards accurate quantification of retinal fluid.
Details
- Title: Subtitle
- Geodesic Graph Cut Based Retinal Fluid Segmentation in Optical Coherence Tomography
- Creators
- Hrvoje BogunovićMichael D Abràmoff - University of Iowa, Ophthalmology and Visual SciencesMilan Sonka - University of Iowa, Electrical and Computer Engineering
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the Ophthalmic Medical Image Analysis Second International Workshop, OMIA 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 9, 2015, pp.49-56
- Conference
- Munich, Germany
- DOI
- 10.17077/omia.1026
- Publisher
- University of Iowa; Iowa City, Iowa
- Copyright
- Copyright © 2015 Hrvoje Bogunović, Michael D. Abràmoff, and Milan Sonka
- Language
- English
- Date published
- 10/2015
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984054299602771
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