activity
20182023
most citedEarly Melanoma Diagnosis with Sequential Dermoscopic Images

75 citations · 126 across the 17 of their papers we have counts for

collaborators

22 papers

cs.CV2023★ 1 cited

Universal Semi-Supervised Learning for Medical Image Classification

Lie Ju, Yicheng Wu, Wei Feng +4

Semi-supervised learning (SSL) has attracted much attention since it reduces the expensive costs of collecting adequate well-labeled training data, especially for deep learning met…

cs.CV2023★ 2 cited

EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition

Siyuan Yan, Chi Liu, Zhen Yu +6

Skin lesion recognition using deep learning has made remarkable progress, and there is an increasing need for deploying these systems in real-world scenarios. However, recent resea…

cs.CV2023★ 2 cited

Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decision

Siyuan Yan, Zhen Yu, Xuelin Zhang +5

Deep neural networks have demonstrated promising performance on image recognition tasks. However, they may heavily rely on confounding factors, using irrelevant artifacts or bias w…

cs.CV2022

Multimorbidity Content-Based Medical Image Retrieval Using Proxies

Yunyan Xing, Benjamin J. Meyer, Mehrtash Harandi +2

Content-based medical image retrieval is an important diagnostic tool that improves the explainability of computer-aided diagnosis systems and provides decision making support to h…

eess.IV2022★ 2 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…