44 citations · 45 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.IV2022★ 44 cited
A deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography
Roy Schwartz, Hagar Khalid, Sandra Liakopoulos +12
Purpose - To develop and validate a deep learning (DL) framework for the detection and quantification of drusen and reticular pseudodrusen (RPD) on optical coherence tomography sca…