Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images.
Publication
, Journal Article
Keller, B; Cunefare, D; Grewal, DS; Mahmoud, TH; Izatt, JA; Farsiu, S
Published in: J Biomed Opt
July 1, 2016
We introduce a metric in graph search and demonstrate its application for segmenting retinal optical coherence tomography (OCT) images of macular pathology. Our proposed “adjusted mean arc length” (AMAL) metric is an adaptation of the lowest mean arc length search technique for automated OCT segmentation. We compare this method to Dijkstra’s shortest path algorithm, which we utilized previously in our popular graph theory and dynamic programming segmentation technique. As an illustrative example, we show that AMAL-based length-adaptive segmentation outperforms the shortest path in delineating the retina/vitreous boundary of patients with full-thickness macular holes when compared with expert manual grading.
Duke Scholars
Published In
J Biomed Opt
DOI
EISSN
1560-2281
Publication Date
July 1, 2016
Volume
21
Issue
7
Start / End Page
76015
Location
United States
Related Subject Headings
- Tomography, Optical Coherence
- Optics
- Macular Degeneration
- Humans
- Algorithms
- 5102 Atomic, molecular and optical physics
- 4003 Biomedical engineering
- 3212 Ophthalmology and optometry
- 1113 Opthalmology and Optometry
- 0903 Biomedical Engineering
Citation
APA
Chicago
ICMJE
MLA
NLM
Keller, B., Cunefare, D., Grewal, D. S., Mahmoud, T. H., Izatt, J. A., & Farsiu, S. (2016). Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images. J Biomed Opt, 21(7), 76015. https://doi.org/10.1117/1.JBO.21.7.076015
Keller, Brenton, David Cunefare, Dilraj S. Grewal, Tamer H. Mahmoud, Joseph A. Izatt, and Sina Farsiu. “Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images.” J Biomed Opt 21, no. 7 (July 1, 2016): 76015. https://doi.org/10.1117/1.JBO.21.7.076015.
Keller B, Cunefare D, Grewal DS, Mahmoud TH, Izatt JA, Farsiu S. Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images. J Biomed Opt. 2016 Jul 1;21(7):76015.
Keller, Brenton, et al. “Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images.” J Biomed Opt, vol. 21, no. 7, July 2016, p. 76015. Pubmed, doi:10.1117/1.JBO.21.7.076015.
Keller B, Cunefare D, Grewal DS, Mahmoud TH, Izatt JA, Farsiu S. Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images. J Biomed Opt. 2016 Jul 1;21(7):76015.
Published In
J Biomed Opt
DOI
EISSN
1560-2281
Publication Date
July 1, 2016
Volume
21
Issue
7
Start / End Page
76015
Location
United States
Related Subject Headings
- Tomography, Optical Coherence
- Optics
- Macular Degeneration
- Humans
- Algorithms
- 5102 Atomic, molecular and optical physics
- 4003 Biomedical engineering
- 3212 Ophthalmology and optometry
- 1113 Opthalmology and Optometry
- 0903 Biomedical Engineering