1 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
A unified multi-task framework enables interpretable chest radiograph analysis
Lijian Xu, Ziyu Ni, Xinglong Liu +3
While multimodal deep learning has advanced medical imaging analysis, existing black-box systems \textcolor{black}{may remain confined to isolated tasks, often overlooking} the tru…
Hypergraph Mamba for Efficient Whole Slide Image Understanding
Jiaxuan Lu, Yuhui Lin, Junyan Shi +4
Whole Slide Images (WSIs) in histopathology pose a significant challenge for extensive medical image analysis due to their ultra-high resolution, massive scale, and intricate spati…
Multi-modal Vision Pre-training for Medical Image Analysis
Shaohao Rui, Lingzhi Chen, Zhenyu Tang +4
Self-supervised learning has greatly facilitated medical image analysis by suppressing the training data requirement for real-world applications. Current paradigms predominantly re…
Pathology-knowledge Enhanced Multi-instance Prompt Learning for Few-shot Whole Slide Image Classification
Linhao Qu, Dingkang Yang, Dan Huang +4
Current multi-instance learning algorithms for pathology image analysis often require a substantial number of Whole Slide Images for effective training but exhibit suboptimal perfo…