The goal of our project """"""""Automated Screening for Diabetic Retinopathy by Content"""""""" (R01 EY017065) is to investigate the feasibility of using content-based image retrieval to detect and accurately describe and index human retinal disease, specifically diabetic retinopathy, collected remotely from low-cost, non-dilated retinal photographs. Content-based image retrieval (CBIR) is the process of retrieving related images from very large database collections, based upon their pictorial content. Our conceptual hypothesis predicts that by extracting features from digital images (content information) and comparing the image and associated metadata (contextual information) to similar, validated images retrieved from a large compiled retinal image library, computer-based, (i.e. automated) diagnostic capabilities would emerge. Using CBIR, we have successfully developed a web-based method that permits remote diagnosis of DR in the primary care health setting, in real time, through remote access to a computer-based, diagnostic, image analysis method. The studies we propose in this competitive renewal are designed to address key methods in the performance of automated machine segmentation by our current algorithms. Our goal is to improve the performance to a level which will permit implementation as a fully automated patient care paradigm with expert capabilities that yield the highest possible sensitivity and specificity of disease detection. We will also compile a library large enough to validate our hypothesis that clinical metadata (contextual data) can contribute to the performance (sensitivity and specificity) of the CBIR method to provide a robust diagnostic method for remote detection and diagnosis of DR.
By 2030 it will be necessary to examine 1 million patients for diabetic eye disease every day worldwide. Treatment for DR is available;our challenge lies in finding a cost-effective approach to detecting and managing diabetic eye disease in large populations. The application of computer-based imaging to the diagnosis of retinal disease, using novel image analysis and clinical metadata algorithms hold the promise of achieving low-cost, automated, diagnostic methods to improve community eye health through access to image-based """"""""expert"""""""" diagnosis for underserved patients in rapidly expanding at-risk populations.
| 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 |
| 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 |
| 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, 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 |
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