Automatic Anterior Chamber Angle Structure Segmentation in AS-OCT Image based on Label Transfer

Automatic Anterior Chamber Angle Structure Segmentation in AS-OCT Image based on Label Transfer
Title:
Automatic Anterior Chamber Angle Structure Segmentation in AS-OCT Image based on Label Transfer
Other Titles:
International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DOI:
10.1109/EMBC.2016.7590942
Keywords:
Publication Date:
16 August 2016
Citation:
H. Fu et al., "Automatic anterior chamber angle structure segmentation in AS-OCT image based on label transfer," 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, 2016, pp. 1288-1291. doi: 10.1109/EMBC.2016.7590942
Abstract:
The anterior chamber angle (ACA) plays an important role for diagnosis and treatment of angle-closure glaucoma. Anterior Segment Optical Coherence Tomography (AS-OCT) imaging is qualitative and quantitative assessment for the ACA structure. In this paper, we propose a novel fully automatic segmentation method for anterior chamber angle structure in AS-OCT. In our method, the initial labels are obtained by using label transfer from the AS-OCT reference dataset. Then, these labels are refined and utilized as the landmarks to support the structure segmentation. Finally, the major clinical structures: corneal boundary, iris region, and trabecular-iris contact, are extracted as the segmentation result. Experiments show that our proposed method achieve the satisfactory segmentation performance on the clinical AS-OCT dataset. Our proposed method has potential in the applications of clinical ACA parameter measurement and automatic glaucoma classification.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISSN:
1558-4615
Files uploaded: