67 citations · 68 across the 2 of their papers we have counts for
2 papers
eess.IV2023★ 1 cited
Uncertainty-Aware Multiple-Instance Learning for Reliable Classification: Application to Optical Coherence Tomography
Coen de Vente, Bram van Ginneken, Carel B. Hoyng +2
Deep learning classification models for medical image analysis often perform well on data from scanners that were used during training. However, when these models are applied to da…
eess.IV2019★ 67 cited
A deep learning model for segmentation of geographic atrophy to study its long-term natural history
Bart Liefers, Johanna M. Colijn, Cristina González-Gonzalo +6
Purpose: To develop and validate a deep learning model for automatic segmentation of geographic atrophy (GA) in color fundus images (CFIs) and its application to study growth rate…