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Proceedings Article

Collaborative SDOCT segmentation and analysis software

[+] Author Affiliations
Yeyi Yun, Aaron Carass, Andrew Lang, Jerry L. Prince, Bhavna J. Antony

The Johns Hopkins Univ. (United States)

Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 1013813 (March 13, 2017); doi:10.1117/12.2254050
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From Conference Volume 10138

  • Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications
  • Tessa S. Cook; Jianguo Zhang
  • Orlando, Florida, United States | February 11, 2017

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. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Yeyi Yun ; Aaron Carass ; Andrew Lang ; Jerry L. Prince and Bhavna J. Antony
" Collaborative SDOCT segmentation and analysis software ", Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 1013813 (March 13, 2017); doi:10.1117/12.2254050; http://dx.doi.org/10.1117/12.2254050


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