Improving graph-based OCT segmentation for severe pathology in retinitis pigmentosa patients

Andrew Lang, Aaron Carass, Ava K. Bittner, Howard S. Ying, Jerry L. Prince

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

Abstract

Three dimensional segmentation of macular optical coherence tomography (OCT) data of subjects with retinitis pigmentosa (RP) is a challenging problem due to the disappearance of the photoreceptor layers, which causes algorithms developed for segmentation of healthy data to perform poorly on RP patients. In this work, we present enhancements to a previously developed graph-based OCT segmentation pipeline to enable processing of RP data. The algorithm segments eight retinal layers in RP data by relaxing constraints on the thickness and smoothness of each layer learned from healthy data. Following from prior work, a random forest classifier is first trained on the RP data to estimate boundary probabilities, which are used by a graph search algorithm to find the optimal set of nine surfaces that fit the data. Due to the intensity disparity between normal layers of healthy controls and layers in various stages of degeneration in RP patients, an additional intensity normalization step is introduced. Leave-one-out validation on data acquired from nine subjects showed an average overall boundary error of 4.22 μm as compared to 6.02 μm using the original algorithm.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2017
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
EditorsBarjor Gimi, Andrzej Krol
PublisherSPIE
ISBN (Electronic)9781510607194
DOIs
StatePublished - 2017
EventMedical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging - Orlando, United States
Duration: Feb 12 2017Feb 14 2017

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10137
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CityOrlando
Period2/12/172/14/17

Keywords

  • OCT
  • Random forest
  • Retina
  • Retinitis pigmentosa
  • Segmentation

ASJC Scopus subject areas

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

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