AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge

1 code implementation • 3 Feb 2023 • Coen de Vente, Koenraad A. Vermeer, Nicolas Jaccard, He Wang, Hongyi Sun, Firas Khader, Daniel Truhn, Temirgali Aimyshev, Yerkebulan Zhanibekuly, Tien-Dung Le, Adrian Galdran, Miguel Ángel González Ballester, Gustavo Carneiro, Devika R G, Hrishikesh P S, Densen Puthussery, Hong Liu, Zekang Yang, Satoshi Kondo, Satoshi Kasai, Edward Wang, Ashritha Durvasula, Jónathan Heras, Miguel Ángel Zapata, Teresa Araújo, Guilherme Aresta, Hrvoje Bogunović, Mustafa Arikan, Yeong Chan Lee, Hyun Bin Cho, Yoon Ho Choi, Abdul Qayyum, Imran Razzak, Bram van Ginneken, Hans G. Lemij, Clara I. Sánchez

Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible.

Out-of-Distribution Detection

DenseUNets with feedback non-local attention for the segmentation of specular microscopy images of the corneal endothelium with guttae

2 code implementations • 3 Mar 2022 • Juan P. Vigueras-Guillén, Jeroen van Rooij, Bart T. H. van Dooren, Hans G. Lemij, Esma Islamaj, Lucas J. van Vliet, Koenraad A. Vermeer

To estimate the corneal endothelial parameters from specular microscopy images depicting cornea guttata (Fuchs dystrophy), we propose a new deep learning methodology that includes a novel attention mechanism named feedback non-local attention (fNLA).

Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study

no code implementations • 4 Jun 2019 • Thomas W. Rogers, Nicolas Jaccard, Francis Carbonaro, Hans G. Lemij, Koenraad A. Vermeer, Nicolaas J. Reus, Sameer Trikha

Objectives: To evaluate the performance of a deep learning based Artificial Intelligence (AI) software for detection of glaucoma from stereoscopic optic disc photographs, and to compare this performance to the performance of a large cohort of ophthalmologists and optometrists.