Samiksha Pachade

TL;DR: The IDRiD (Indian Diabetic Retinopathy Image Dataset), is the first database representative of an Indian population and makes it perfect for development and evaluation of image analysis algorithms for early detection of diabetic retinopathy.

TL;DR: The set-up and results of this challenge that is primarily based on Indian Diabetic Retinopathy Image Dataset (IDRiD), which received a positive response from the scientific community, have the potential to enable new developments in retinal image analysis and image-based DR screening in particular.

TL;DR: The Retinal Fundus Multi-disease Image Dataset (RFMiD) as mentioned in this paper is the only publicly available dataset that constitutes such a wide variety of diseases that appear in routine clinical settings.

TL;DR: Nested EfficientNet (NENet) as discussed by the authors is a segmentation network that combines cross-entropy and dice coefficient (DC) loss to guide the network for accurate segmentation and a modified patch-based discriminator is designed to improve the local segmentation details.

TL;DR: A novel framework to address the issue of retinal blood vessel detection and width measurement under these challenging circumstances and also on two different imaging modalities: color fundus imaging and Scanning Laser Ophthalmoscopy (SLO).