activity
20232026
most citedSegment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentation

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

collaborators

5 papers

cs.CV2026

PAINT: Pathology-Aware Integrated Next-Scale Transformation for Virtual Immunohistochemistry

Rongze Ma, Mengkang Lu, Zhenyu Xiang +4

Virtual immunohistochemistry (IHC) aims to computationally synthesize molecular staining patterns from routine Hematoxylin and Eosin (H\&E) images, offering a cost-effective and ti…

eess.IV2025

Deformable Medical Image Registration with Effective Anatomical Structure Representation and Divide-and-Conquer Network

Xinke Ma, Yongsheng Pan, Qingjie Zeng +4

Effective representation of Regions of Interest (ROI) and independent alignment of these ROIs can significantly enhance the performance of deformable medical image registration (DM…

cs.CV20233 cited

Segment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentation

Qingjie Zeng, Yutong Xie, Zilin Lu +3

Annotation scarcity has become a major obstacle for training powerful deep-learning models for medical image segmentation, restricting their deployment in clinical scenarios. To ad…

cs.CV2023

Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation

Ziyang Chen, Yongsheng Pan, Yiwen Ye +2

Distribution shift widely exists in medical images acquired from different medical centres and poses a significant obstacle to deploying the pre-trained semantic segmentation model…

cs.CV20231 cited

Discrepancy Matters: Learning from Inconsistent Decoder Features for Consistent Semi-supervised Medical Image Segmentation

Qingjie Zeng, Yutong Xie, Zilin Lu +2

Semi-supervised learning (SSL) has been proven beneficial for mitigating the issue of limited labeled data especially on the task of volumetric medical image segmentation. Unlike p…