Application of Deep learning for Detection of Retinal Abnormalities from fundus images – Nitigya Sambyal

Deep learning has emerged as a powerful tool in medical image analysis, particularly in the domain of retinal imaging for diagnosing diabetic retinopathy. Diabetic retinopathy is a common complication of diabetes and a leading cause of blindness in the working population worldwide. Early detection and timely intervention are crucial in preventing vision loss among diabetic patients. Here I will present some deep learning-based solutions for detection and staging of diabetic retinopathy. I will also focus on the automated segmentation of diabetic retinopathy associated retinal lesions like microaneurysms, haemorrhages, hard exudates and soft exudates from fundus images. I will conclude my talk by discussing the limitations and challenges that are critical to realize the full potential of deep learning for improving the delivery of eye care services.