RESEARCH PLAN: COMPUTATIONAL OPHTHALMOLOGY MODULE OVERVIEW At UCSD, structural imaging instruments such as the spectral domain optical coherence tomography (SD-OCT) and functional instruments are used extensively in animal (Drs. Weinreb, Freeman, Yu, La Spada, Zhang, Freeman) and human studies of glaucoma (Drs. Weinreb, Ju, Lindsay, Zangwill, Medeiros, Balasubramanian) and retinal disease (Drs. Freeman, Yu, Bartsch, Zhang, Cheng). The recent development and commercialization of imaging instruments such as SD-OCT has brought a significant improvement in our ability to visualize and measure the retina in-vivo in both animals and humans. These instruments have potential to dramatically improve our ability to understand the histopathology of major eyes diseases including glaucoma, age-related macular degeneration and diabetic retinopathy. These instruments represent a generational leap forward in technological development and several orders of magnitude more data than previous instruments. The challenge facing both ophthalmic clinicians and researchers is how best to utilize the vast quantity of data to 1) enhance our understanding of the histopathology of eye diseases, and 2) identify structural biomarkers of disease and its progression toward the ultimate goal of improving patient management. The computational ophthalmology module will provide essential centralized resources to support the computationally intensive analysis of structural imaging and functional tests used in animal and human vision research studies. This module will provide dedicated computational resources with a capacity to meet high computational demands and software toolkits that leverage these computational resources so that researchers can analyze the complex and data intensive retinal datasets (imaging and functional testing) outside of the proprietary software available with each ophthalmic test.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Center Core Grants (P30)
Project #
5P30EY022589-03
Application #
8689051
Study Section
Special Emphasis Panel (ZEY1-VSN)
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
3
Fiscal Year
2014
Total Cost
$188,364
Indirect Cost
$66,839
Name
University of California San Diego
Department
Type
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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Christopher, Mark; Belghith, Akram; Weinreb, Robert N et al. (2018) Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression. Invest Ophthalmol Vis Sci 59:2748-2756
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Christopher, Mark; Belghith, Akram; Bowd, Christopher et al. (2018) Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs. Sci Rep 8:16685
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Bowd, Christopher; Zangwill, Linda M; Weinreb, Robert N et al. (2018) Racial Differences in Rate of Change of Spectral-Domain Optical Coherence Tomography-Measured Minimum Rim Width and Retinal Nerve Fiber Layer Thickness. Am J Ophthalmol 196:154-164
Ju, Won-Kyu; Shim, Myoung Sup; Kim, Keun-Young et al. (2018) Ubiquinol promotes retinal ganglion cell survival and blocks the apoptotic pathway in ischemic retinal degeneration. Biochem Biophys Res Commun 503:2639-2645
Chekuri, Anil; Guru, Aditya A; Biswas, Pooja et al. (2018) IFT88 mutations identified in individuals with non-syndromic recessive retinal degeneration result in abnormal ciliogenesis. Hum Genet 137:447-458
Hou, Huiyuan; Moghimi, Sasan; Zangwill, Linda M et al. (2018) Inter-eye Asymmetry of Optical Coherence Tomography Angiography Vessel Density in Bilateral Glaucoma, Glaucoma Suspect, and Healthy Eyes. Am J Ophthalmol 190:69-77

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