Diabetic retinopathy (DR) is one of the main reasons of preventable blindness globally. Performing retinal examinations on all diabetic patients is an unmet need, and detection at an early stage can offer better control of the disease. The&
Deep Learning Based Diabetic Retinopathy Detection Using Optical Coherence Tomography
Diabetic retinopathy (DR) is one of the main reasons of preventable blindness globally. Performing retinal examinations on all diabetic patients is an unmet need, and detection at an early stage can offer better control of the disease. The goal of this project is to offer an optical coherence tomography (OCT) image based diagnostic technology for automated early DR diagnosis. This project can help ophthalmologists with evaluation and treatment, reducing the rate of vision loss, and enabling timely and accurate diagnosis.
A deep learning based model is to be designed which is able to diagnose Diabetic retinopathy in OCT(Optical Coherence Tomogrpahy) images. The complete implementation of the project is depicted in the block diagam
Beneficiaries
A web based portal built with web technologies HTML, CSS, JS, Python(Flask) which is integrated with our Deep Learning Model that will diagnose diabetic retnopathy in OCT images
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Graphics Processing Unit (GPU) | Equipment | 1 | 68000 | 68000 |
| Deployment Server Services | Miscellaneous | 1 | 8000 | 8000 |
| Miscellaneous | Miscellaneous | 1 | 2000 | 2000 |
| Total in (Rs) | 78000 |
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