title: Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology.
abstract: Accurate quantification of retinal layer thicknesses in mice as seen on optical coherence tomography (OCT) is crucial for the study of numerous ocular and neurological diseases. However, manual segmentation is time-consuming and subjective. Previous attempts to automate this process were limited to high-quality scans from mice with no missing layers or visible pathology. This paper presents an automatic approach for segmenting retinal layers in spectral domain OCT images using sparsity based denoising, support vector machines, graph theory, and dynamic programming (S-GTDP). Results show that this method accurately segments all present retinal layer boundaries, which can range from seven to ten, in wild-type and rhodopsin knockout mice as compared to manual segmentation and has a more accurate performance as compared to the commercial automated Diver segmentation software.
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham 27708, USA ; Department of Computer Science, Duke University, Durham 27708, USA.
authors.forename: Pratul P
authors.initials: PP
authors.lastname: Srinivasan
authors.affiliation: Department of Ophthalmology, Duke University Medical Center, Durham 27710, USA.
authors.forename: Stephanie J
authors.initials: SJ
authors.lastname: Heflin
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham 27708, USA ; Department of Ophthalmology, Duke University Medical Center, Durham 27710, USA.
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Izatt
authors.affiliation: Department of Ophthalmology, Duke University Medical Center, Durham 27710, USA ; Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham 27710, USA.
authors.forename: Vadim Y
authors.initials: VY
authors.lastname: Arshavsky
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham 27708, USA ; Department of Ophthalmology, Duke University Medical Center, Durham 27710, USA ; Department of Electrical and Computer Engineering, Duke University, Durham 27708, USA ; Department of Computer Science, Duke University, Durham 27708, USA.
authors.forename: Sina
authors.initials: S
authors.lastname: Farsiu
keywords: (100.0100) Image processing; (100.2960) Image analysis; (100.5010) Pattern recognition; (110.4500) Optical coherence tomography; (170.4470) Ophthalmology