The application of computer-based imaging to the diagnosis of retinal disease is rapidly becoming a reality. Advances in the imaging of ocular anatomy and pathology can now provide data to diagnose and quantify specific diseases including diabetic retinopathy. The potential for these digital technologies is clear, new computer based systems, and diagnostic algorithms hold the promise of producing low-cost, potentially automated, diagnostic imaging systems. The goal of this project is to investigate the feasibility of a content-based image retrieval (CBIR) method to accurately describe and index human retinal images of diabetic retinopathy collected from low-cost, nondilated retinal photographic examinations. Our goal is to demonstrate the feature-based indexing and retrieval process of CBIR and verify our hypothesis, and novel concept, that retinal pathology can be identified and quantified from visually similar retinal images assembled from a large database comprising images of diabetic retinopathy. The proposed research extends this fundamental investigation by incorporating intrinsic and extrinsic patient data to provide a diagnostic method. We have brought together a unique team that is currently designing the algorithms, developing the analytical tools, and performing the required clinical trials to reach the stated goals of this RFA.
| Karnowski, Thomas P; Giancardo, Luca; Li, Yaqin et al. (2013) Retina image analysis and ocular telehealth: the Oak Ridge National Laboratory-Hamilton Eye Institute case study. Conf Proc IEEE Eng Med Biol Soc 2013:7140-3 |
| Trucco, Emanuele; Ruggeri, Alfredo; Karnowski, Thomas et al. (2013) Validating retinal fundus image analysis algorithms: issues and a proposal. Invest Ophthalmol Vis Sci 54:3546-59 |
| Paquit, Vincent C; Karnowski, Thomas P; Aykac, Deniz et al. (2012) Detecting flash artifacts in fundus imagery. Conf Proc IEEE Eng Med Biol Soc 2012:1442-5 |
| Giancardo, Luca; Meriaudeau, Fabrice; Karnowski, Thomas P et al. (2012) Exudate-based diabetic macular edema detection in fundus images using publicly available datasets. Med Image Anal 16:216-26 |
| Garg, Seema; Jani, Pooja D; Kshirsagar, Abhijit V et al. (2012) Telemedicine and retinal imaging for improving diabetic retinopathy evaluation. Arch Intern Med 172:1677-8 |
| Giancardo, L; Meriaudeau, F; Karnowski, T P et al. (2011) Microaneurysm detection with radon transform-based classification on retina images. Conf Proc IEEE Eng Med Biol Soc 2011:5939-42 |
| Gangaputra, Sapna; Almukhtar, Talat; Glassman, Adam R et al. (2011) Comparison of film and digital fundus photographs in eyes of individuals with diabetes mellitus. Invest Ophthalmol Vis Sci 52:6168-73 |
| Li, Helen K; Horton, Mark; Bursell, Sven-Erik et al. (2011) Telehealth practice recommendations for diabetic retinopathy, second edition. Telemed J E Health 17:814-37 |
| Santos-Villalobos, H; Karnowski, T P; Aykac, D et al. (2011) Statistical characterization and segmentation of drusen in fundus images. Conf Proc IEEE Eng Med Biol Soc 2011:6236-41 |
| Li, Yaqin; Karnowski, Thomas P; Tobin, Kenneth W et al. (2011) A health insurance portability and accountability act-compliant ocular telehealth network for the remote diagnosis and management of diabetic retinopathy. Telemed J E Health 17:627-34 |
Showing the most recent 10 out of 17 publications
