Longitudinal graph-based segmentation of macular OCT using fundus alignment

Andrew Lang, Aaron Carass, Omar Al-Louzi, Pavan Bhargava, Howard S. Ying, Peter Calabresi, Jerry Ladd Prince

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Segmentation of retinal layers in optical coherence tomography (OCT) has become an important diagnostic tool for a variety of ocular and neurological diseases. Currently all OCT segmentation algorithms analyze data independently, ignoring previous scans, which can lead to spurious measurements due to algorithm variability and failure to identify subtle changes in retinal layers. In this paper, we present a graph-based segmentation framework to provide consistent longitudinal segmentation results. Regularization over time is accomplished by adding weighted edges between corresponding voxels at each visit. We align the scans to a common subject space before connecting the graphs by registering the data using both the retinal vasculature and retinal thickness generated from a low resolution segmentation. This initial segmentation also allows the higher dimensional temporal problem to be solved more efficiently by reducing the graph size. Validation is performed on longitudinal data from 24 subjects, where we explore the variability between our longitudinal graph method and a cross-sectional graph approach. Our results demonstrate that the longitudinal component improves segmentation consistency, particularly in areas where the boundaries are difficult to visualize due to poor scan quality.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2015: Image Processing
PublisherSPIE
Volume9413
ISBN (Print)9781628415032
DOIs
StatePublished - 2015
EventMedical Imaging 2015: Image Processing - Orlando, United States
Duration: Feb 24 2015Feb 26 2015

Other

OtherMedical Imaging 2015: Image Processing
CountryUnited States
CityOrlando
Period2/24/152/26/15

Fingerprint

Optical tomography
Optical Coherence Tomography
tomography
alignment
Eye Diseases

Keywords

  • layer segmentation
  • longitudinal
  • OCT
  • retina

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Lang, A., Carass, A., Al-Louzi, O., Bhargava, P., Ying, H. S., Calabresi, P., & Prince, J. L. (2015). Longitudinal graph-based segmentation of macular OCT using fundus alignment. In Medical Imaging 2015: Image Processing (Vol. 9413). [94130M] SPIE. https://doi.org/10.1117/12.2077713

Longitudinal graph-based segmentation of macular OCT using fundus alignment. / Lang, Andrew; Carass, Aaron; Al-Louzi, Omar; Bhargava, Pavan; Ying, Howard S.; Calabresi, Peter; Prince, Jerry Ladd.

Medical Imaging 2015: Image Processing. Vol. 9413 SPIE, 2015. 94130M.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lang, A, Carass, A, Al-Louzi, O, Bhargava, P, Ying, HS, Calabresi, P & Prince, JL 2015, Longitudinal graph-based segmentation of macular OCT using fundus alignment. in Medical Imaging 2015: Image Processing. vol. 9413, 94130M, SPIE, Medical Imaging 2015: Image Processing, Orlando, United States, 2/24/15. https://doi.org/10.1117/12.2077713
Lang A, Carass A, Al-Louzi O, Bhargava P, Ying HS, Calabresi P et al. Longitudinal graph-based segmentation of macular OCT using fundus alignment. In Medical Imaging 2015: Image Processing. Vol. 9413. SPIE. 2015. 94130M https://doi.org/10.1117/12.2077713
Lang, Andrew ; Carass, Aaron ; Al-Louzi, Omar ; Bhargava, Pavan ; Ying, Howard S. ; Calabresi, Peter ; Prince, Jerry Ladd. / Longitudinal graph-based segmentation of macular OCT using fundus alignment. Medical Imaging 2015: Image Processing. Vol. 9413 SPIE, 2015.
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