activity
20162025
most citedVoxResNet: Deep Voxelwise Residual Networks for Volumetric Brain Segmentation

115 citations · 136 across the 8 of their papers we have counts for

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Showing cs.CVShow all

12 papers · 1 filter

cs.CV2024

Memory-Efficient Prompt Tuning for Incremental Histopathology Classification

Yu Zhu, Kang Li, Lequan Yu +1

Recent studies have made remarkable progress in histopathology classification. Based on current successes, contemporary works proposed to further upgrade the model towards a more g…

cs.CV202314 cited

IDRNet: Intervention-Driven Relation Network for Semantic Segmentation

Zhenchao Jin, Xiaowei Hu, Lingting Zhu +3

Co-occurrent visual patterns suggest that pixel relation modeling facilitates dense prediction tasks, which inspires the development of numerous context modeling paradigms, \emph{e…

cs.CV20232 cited

HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis

Ziyu Guo, Weiqin Zhao, Shujun Wang +1

In computation pathology, the pyramid structure of gigapixel Whole Slide Images (WSIs) has recently been studied for capturing various information from individual cell interactions…

cs.CV20239 cited

Cheap Lunch for Medical Image Segmentation by Fine-tuning SAM on Few Exemplars

Weijia Feng, Lingting Zhu, Lequan Yu

The Segment Anything Model (SAM) has demonstrated remarkable capabilities of scaled-up segmentation models, enabling zero-shot generalization across a variety of domains. By levera…

cs.CV20232 cited

ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis

Yanyan Huang, Weiqin Zhao, Shujun Wang +3

Whole slide image (WSI) analysis has become increasingly important in the medical imaging community, enabling automated and objective diagnosis, prognosis, and therapeutic-response…

cs.CV20231 cited

Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation

Qingyue Wei, Lequan Yu, Xianhang Li +4

Medical imaging has witnessed remarkable progress but usually requires a large amount of high-quality annotated data which is time-consuming and costly to obtain. To alleviate this…