44 citations · 45 across the 3 of their papers we have counts for
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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…
eess.IV2021
Unsupervised cross domain learning with applications to 7 layer segmentation of OCTs
Yue Wu, Abraham Olvera Barrios, Ryan Yanagihara +4
Unsupervised cross domain adaptation for OCT 7 layer segmentation and other medical applications where labeled training data is only available in a source domain and unavailable in…