most citedADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images

80 citations · 83 across the 4 of their papers we have counts for

collaborators

5 papers

eess.IV20222 cited

Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters

Junde Wu, Huihui Fang, Yehui Yang +5

In medical image segmentation, it is often necessary to collect opinions from multiple experts to make the final decision. This clinical routine helps to mitigate individual bias.…

cs.CV20221 cited

ExpNet: A unified network for Expert-Level Classification

Junde Wu, Huihui Fang, Yehui Yang +4

Different from the general visual classification, some classification tasks are more challenging as they need the professional categories of the images. In the paper, we call them…

eess.IV2022

Learning to screen Glaucoma like the ophthalmologists

Junde Wu, Huihui Fang, Fei Li +2

GAMMA Challenge is organized to encourage the AI models to screen the glaucoma from a combination of 2D fundus image and 3D optical coherence tomography volume, like the ophthalmol…

eess.IV202280 cited

ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images

Huihui Fang, Fei Li, Huazhu Fu +28

Age-related macular degeneration (AMD) is the leading cause of visual impairment among elderly in the world. Early detection of AMD is of great importance, as the vision loss cause…

cs.CV2018

Greedy Graph Searching for Vascular Tracking in Angiographic Image Sequences

Huihui Fang, Jian Yang, Jianjun Zhu +5

Vascular tracking of angiographic image sequences is one of the most clinically important tasks in the diagnostic assessment and interventional guidance of cardiac disease. However…