@inproceedings{85f623b271104f78806213cf3c6c2aa8,
title = "Longitudinal graph-based segmentation of macular OCT using fundus alignment",
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.",
keywords = "OCT, layer segmentation, longitudinal, retina",
author = "Andrew Lang and Aaron Carass and Omar Al-Louzi and Pavan Bhargava and Ying, {Howard S.} and Calabresi, {Peter A.} and Prince, {Jerry L.}",
note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; Medical Imaging 2015: Image Processing ; Conference date: 24-02-2015 Through 26-02-2015",
year = "2015",
doi = "10.1117/12.2077713",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Styner, {Martin A.} and Sebastien Ourselin",
booktitle = "Medical Imaging 2015",
}