Detection and Grade Classification of Diabetic Retinopathy and Adult Vitelliform Macular Dystrophy Based on Ophthalmoscopy Images

Diabetic retinopathy (DR) and adult vitelliform macular dystrophy (AVMD) may cause significant vision impairment or blindness. Prompt diagnosis is essential for patient health. Photographic ophthalmoscopy checks retinal health quickly, painlessly, easily. It a frequent eye test. Ophthalmoscopy images of these two illnesses are challenging to analyse since early indications typically absent. We propose deep learning strategy called ActiveLearn address concerns. This approach relies heavily on the Transformer as its central structure. Furthermore, transfer strategies that able strengthen low-level features model data augmentation balance incorporated owing peculiarities medical pictures, such their limited quantity generally rigid On benchmark dataset, suggested technique shown perform better than state-of-the-art methods in both binary multiclass accuracy classification tasks with scores 97.9% 97.1%, respectively.