Abstract

Computational Ophthalmology Core The Computational Ophthalmology Core provides high-performance computing resources and state-of-the- art custom computer programming to UCSD vision researchers completing cellular, animal, and human vision research studies. The data analysis requirements of the vision research community are increasing exponentially as high resolution retinal imaging datasets become the standard, and genomics research utilizes exome and whole genome sequencing. The powerful CPU and GPU computational condo clusters managed by the San Diego Supercomputer Center, the immersive 3-D visualization facility, and custom software tools provided by this core facilitate analysis of these large datasets. The Computational Ophthalmology core also supports a computer programmer with image analysis and signal processing expertise to develop image analysis software toolkits, and to support computational analyses of both basic science and clinical vision research projects. In addition, essential IT services such as automated off-site backup, fileservers for secure file-sharing and institutional software licenses (MATLAB, FilemakerPro, Github, FreezerPro) are provided by the Computational Ophthalmology Core to the UCSD vision research community.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Center Core Grants (P30)
Project #
2P30EY022589-06A1
Application #
9573254
Study Section
Special Emphasis Panel (ZEY1)
Project Start
Project End
Budget Start
2018-08-01
Budget End
2019-06-30
Support Year
6
Fiscal Year
2018
Total Cost
Indirect Cost

  Institution

Name
University of California, San Diego
Department
Type
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093

  Publications

Manalastas, Patricia I C; Zangwill, Linda M; Daga, Fabio B et al. (2018) The Association Between Macula and ONH Optical Coherence Tomography Angiography (OCT-A) Vessel Densities in Glaucoma, Glaucoma Suspect, and Healthy Eyes. J Glaucoma 27:227-232
Muftuoglu, Ilkay Kilic; Ramkumar, Hema L; Bartsch, Dirk-Uwe et al. (2018) QUANTITATIVE ANALYSIS OF THE INNER RETINAL LAYER THICKNESSES IN AGE-RELATED MACULAR DEGENERATION USING CORRECTED OPTICAL COHERENCE TOMOGRAPHY SEGMENTATION. Retina 38:1478-1484
Kabbara, Sami W; Zangwill, Linda M; Mundae, Rusdeep et al. (2018) Comparing optical coherence tomography radial and cube scan patterns for measuring Bruch's membrane opening minimum rim width (BMO-MRW) in glaucoma and healthy eyes: cross-sectional and longitudinal analysis. Br J Ophthalmol 102:344-351
Biswas, Pooja; Naeem, Muhammad Asif; Ali, Muhammad Hassaan et al. (2018) Whole-Exome Sequencing Identifies Novel Variants that Co-segregates with Autosomal Recessive Retinal Degeneration in a Pakistani Pedigree. Adv Exp Med Biol 1074:219-228
Meshi, Amit; Lin, Tiezhu; Dans, Kunny et al. (2018) COMPARISON OF RETINAL PATHOLOGY VISUALIZATION IN MULTISPECTRAL SCANNING LASER IMAGING. Retina :
Penteado, Rafaella C; Zangwill, Linda M; Daga, Fábio B et al. (2018) Optical Coherence Tomography Angiography Macular Vascular Density Measurements and the Central 10-2 Visual Field in Glaucoma. J Glaucoma 27:481-489
Ghahari, Elham; Bowd, Christopher; Zangwill, Linda M et al. (2018) Macular Vessel Density in Glaucomatous Eyes With Focal Lamina Cribrosa Defects. J Glaucoma 27:342-349
Kilic Muftuoglu, Ilkay; Bartsch, Dirk-Uwe; Barteselli, Giulio et al. (2018) VISUALIZATION OF MACULAR PUCKER BY MULTICOLOR SCANNING LASER IMAGING. Retina 38:352-358
Garg, Aakriti; De Moraes, C Gustavo; Cioffi, George A et al. (2018) Baseline 24-2 Central Visual Field Damage Is Predictive of Global Progressive Field Loss. Am J Ophthalmol 187:92-98
Chu, Fang-I; Marín-Franch, Iván; Ramezani, Koosha et al. (2018) Associations between structure and function are different in healthy and glaucomatous eyes. PLoS One 13:e0196814

Showing the most recent 10 out of 266 publications