@inproceedings{da950f66e250424a9bc4c01e9f3f2f00,
title = "Collaborative SDOCT segmentation and analysis software",
abstract = "Spectral domain optical coherence tomography (SDOCT) is routinely used in the management and diagnosis of a variety of ocular diseases. This imaging modality also finds widespread use in research, where quantitative measurements obtained from the images are used to track disease progression. In recent years, the number of available scanners and imaging protocols grown and there is a distinct absence of a unified tool that is capable of visualizing, segmenting, and analyzing the data. This is especially noteworthy in longitudinal studies, where data from older scanners and/or protocols may need to be analyzed. Here, we present a graphical user interface (GUI) that allows users to visualize and analyze SDOCT images obtained from two commonly used scanners. The retinal surfaces in the scans can be segmented using a previously described method, and the retinal layer thicknesses can be compared to a normative database. If necessary, the segmented surfaces can also be corrected and the changes applied. The interface also allows users to import and export retinal layer thickness data to an SQL database, thereby allowing for the collation of data from a number of collaborating sites.",
keywords = "Graphical user interface, Retina, SDOCT, Visualization",
author = "Yeyi Yun and Aaron Carass and Andrew Lang and Prince, {Jerry L.} and Antony, {Bhavna J.}",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications ; Conference date: 15-02-2017 Through 16-02-2017",
year = "2017",
doi = "10.1117/12.2254050",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Cook, {Tessa S.} and Jianguo Zhang",
booktitle = "Medical Imaging 2017",
}