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most citedPoisson Ordinal Network for Gleason Group Estimation Using Bi-Parametric MRI

1 citations · 1 across the 8 of their papers we have counts for

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cs.CV2026

Topology-Driven Transferability Estimation for 3D Medical Vision Foundation Models

Jiaqi Tang, Shaoyang Zhang, Fandong Zhang +3

The growing number of medical vision foundation models highlights the need for effective model selection. However, mainstream selection methods rely on exhaustive fine-tuning, whic…

cs.CV2026

TriDP-PTM: a three-stage distortion-perception tradeoff guides the pre-training model for radar cardiac sensing

Jinye Li, Aidong Men, Yang Liu +1

Cardiovascular diseases (CVDs) remain a leading cause of death globally, necessitating continuous, accurate non-invasive cardiac monitoring. While non-contact radar-based approache…

cs.CV2026

3D MRI Image Pretraining via Controllable 2D Slice Navigation Task

Yu Wang, Qingchao Chen

Self-supervised pretraining has become the mainstream approach for learning MRI representations from unlabeled scans. However, most existing objectives still treat each scan primar…

cs.CV2026

The Texture-Shape Dilemma: Boundary-Safe Synthetic Generation for 3D Medical Transformers

Jiaqi Tang, Weixuan Xu, Shu Zhang +2

Vision Transformers (ViTs) have revolutionized medical image analysis, yet their data-hungry nature clashes with the scarcity and privacy constraints of clinical archives. Formula-…

cs.CV2026

Fake It Right: Injecting Anatomical Logic into Synthetic Supervised Pre-training for Medical Segmentation

Jiaqi Tang, Mengyan Zheng, Shu Zhang +2

Vision Transformers (ViTs) excel in 3D medical segmentation but require massive annotated datasets. While Self-Supervised Learning (SSL) mitigates this using unlabeled data, it sti…

cs.CV2025

Locating and Mitigating Gradient Conflicts in Point Cloud Domain Adaptation via Saliency Map Skewness

Jiaqi Tang, Yinsong Xu, Qingchao Chen

Object classification models utilizing point cloud data are fundamental for 3D media understanding, yet they often struggle with unseen or out-of-distribution (OOD) scenarios. Exis…