papers

Publications (5)

eess.IV2026

DaX: Learning General Pathology Representations Across Scales

Bokai Zhao, Yiyang Zhang, Long Bai +3

Computational pathology requires visual representations that transfer across diverse clinical endpoints and remain robust to variation in magnification, staining, scanner type, sli…

cs.CV2026

Benchmarking Pathology Foundation Models for Spatial Domain Understanding

Bokai Zhao, Yiyang Zhang, Yuanchi Zhu +6

Pathology foundation models (PFMs) have emerged as a core approach for learning transferable representations from whole slide images (WSIs), and they are typically benchmarked thro…

cs.CV2026

UniReg: A Universal Model for Controllable CT Image Registration

Zi Li, Jianpeng Zhang, Tai Ma +7

Learning-based medical image registration has matched the accuracy of conventional methods while offering superior computational efficiency. However, existing approaches suffer fro…

cs.CV2026

iPEAR: Iterative Pyramid Estimation with Attention and Residuals for Deformable Medical Image Registration

Heming Wu, Di Wang, Tai Ma +6

Existing pyramid registration networks may accumulate anatomical misalignments and lack an effective mechanism to dynamically determine the number of optimization iterations under…

eess.IV2025

Leveraging Semantic Asymmetry for Precise Gross Tumor Volume Segmentation of Nasopharyngeal Carcinoma in Planning CT

Zi Li, Ying Chen, Zeli Chen +12

In the radiation therapy of nasopharyngeal carcinoma (NPC), clinicians typically delineate the gross tumor volume (GTV) using non-contrast planning computed tomography to ensure ac…