activity
20232026
most citedCAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor Segmentation

2 citations · 4 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

SafeMed-R1: Clinician-Audited Safety and Ethics Alignment for Medical Large Language Models

Chao Ding, Mouxiao Bian, Tianbin Li +12

Large language models(LLMs) increasingly match expert performance on licensing examinations, yet routine clinical use remains limited because governance requires auditable reasonin…

cs.CV2025

ROFI: A Deep Learning-Based Ophthalmic Sign-Preserving and Reversible Patient Face Anonymizer

Yuan Tian, Min Zhou, Yitong Chen +19

Patient face images provide a convenient mean for evaluating eye diseases, while also raising privacy concerns. Here, we introduce ROFI, a deep learning-based privacy protection fr…

cs.CV2025

Semantics versus Identity: A Divide-and-Conquer Approach towards Adjustable Medical Image De-Identification

Yuan Tian, Shuo Wang, Rongzhao Zhang +8

Medical imaging has significantly advanced computer-aided diagnosis, yet its re-identification (ReID) risks raise critical privacy concerns, calling for de-identification (DeID) te…

cs.CV2025

Towards All-in-One Medical Image Re-Identification

Yuan Tian, Kaiyuan Ji, Rongzhao Zhang +4

Medical image re-identification (MedReID) is under-explored so far, despite its critical applications in personalized healthcare and privacy protection. In this paper, we introduce…

cs.CV2024

CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor Segmentation

Zhongzhen Huang, Yankai Jiang, Rongzhao Zhang +2

Existing promptable segmentation methods in the medical imaging field primarily consider either textual or visual prompts to segment relevant objects, yet they often fall short whe…

eess.IV2024

GuideGen: A Text-Guided Framework for Paired Full-torso Anatomy and CT Volume Generation

Linrui Dai, Rongzhao Zhang, Yongrui Yu +1

The recently emerging conditional diffusion models seem promising for mitigating the labor and expenses in building large 3D medical imaging datasets. However, previous studies on…