activity
20202022
most citedLeveraging Regular Fundus Images for Training UWF Fundus Diagnosis Models via Adversarial Learning and Pseudo-Labeling

53 citations · 63 across the 6 of their papers we have counts for

collaborators
Showing eess.IVShow all

5 papers · 1 filter

eess.IV20222 cited

3D Matting: A Benchmark Study on Soft Segmentation Method for Pulmonary Nodules Applied in Computed Tomography

Lin Wang, Xiufen Ye, Donghao Zhang +9

Usually, lesions are not isolated but are associated with the surrounding tissues. For example, the growth of a tumour can depend on or infiltrate into the surrounding tissues. Due…

eess.IV2022

3D Matting: A Soft Segmentation Method Applied in Computed Tomography

Lin Wang, Xiufen Ye, Donghao Zhang +7

Three-dimensional (3D) images, such as CT, MRI, and PET, are common in medical imaging applications and important in clinical diagnosis. Semantic ambiguity is a typical feature of…

eess.IV20214 cited

Evaluation of Various Open-Set Medical Imaging Tasks with Deep Neural Networks

Zongyuan Ge, Xin Wang

The current generation of deep neural networks has achieved close-to-human results on "closed-set" image recognition; that is, the classes being evaluated overlap with the training…

eess.IV20213 cited

Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization

Wei Feng, Lie Ju, Lin Wang +5

Retinal vessel segmentation plays a key role in computer-aided screening, diagnosis, and treatment of various cardiovascular and ophthalmic diseases. Recently, deep learning-based…

eess.IV2020

Bridge the Domain Gap Between Ultra-wide-field and Traditional Fundus Images via Adversarial Domain Adaptation

Lie Ju, Xin Wang, Quan Zhou +5

For decades, advances in retinal imaging technology have enabled effective diagnosis and management of retinal disease using fundus cameras. Recently, ultra-wide-field (UWF) fundus…