most citedA deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography

44 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

4 papers

eess.IV2024

Choroidal Vessel Segmentation on Indocyanine Green Angiography Images via Human-in-the-Loop Labeling

Ruoyu Chen, Ziwei Zhao, Mayinuer Yusufu +3

Human-in-the-loop (HITL) strategy has been recently introduced into the field of medical image processing. Indocyanine green angiography (ICGA) stands as a well-established examina…

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.IV2022★ 18 cited

Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization

Guilherme C. Oliveira, Gustavo H. Rosa, Daniel C. G. Pedronette +4

Deep learning applications for assessing medical images are limited because the datasets are often small and imbalanced. The use of synthetic data has been proposed in the literatu…

cs.CV2022★ 2 cited

Label uncertainty-guided multi-stream model for disease screening

Chi Liu, Zongyuan Ge, Mingguang He +1

The annotation of disease severity for medical image datasets often relies on collaborative decisions from multiple human graders. The intra-observer variability derived from indiv…