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20232026
most citedMPBD-LSTM: A Predictive Model for Colorectal Liver Metastases Using Time Series Multi-phase Contrast-Enhanced CT Scans

2 citations · 2 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Text Over Image: Auditing Multimodal Robustness in Synthetic Medical Image Detection

Ching-Hao Chiu, Hao-Wei Chung, Gelei Xu +7

With the rapid adoption of generative AI, synthetic medical images pose growing risks, including diagnostic deception and insurance fraud. Although prior work has explored vision-l…

cs.CV2026

TopoAgent: An Agentic Framework for Automated Topology Learning in Medical Imaging

Guangyu Meng, Pengfei Gu, Xueyang Li +3

Topological data analysis (TDA), particularly persistent homology (PH), captures geometric structural properties in medical images (e.g., connected components, loops, shape charact…

cs.CV2025

H-CNN-ViT: A Hierarchical Gated Attention Multi-Branch Model for Bladder Cancer Recurrence Prediction

Xueyang Li, Zongren Wang, Yuliang Zhang +6

Bladder cancer is one of the most prevalent malignancies worldwide, with a recurrence rate of up to 78%, necessitating accurate post-operative monitoring for effective patient mana…

cs.CV2025

Incorporating Rather Than Eliminating: Achieving Fairness for Skin Disease Diagnosis Through Group-Specific Expert

Gelei Xu, Yuying Duan, Zheyuan Liu +5

AI-based systems have achieved high accuracy in skin disease diagnostics but often exhibit biases across demographic groups, leading to inequitable healthcare outcomes and diminish…

cs.CV2025

Unsupervised Out-of-Distribution Detection in Medical Imaging Using Multi-Exit Class Activation Maps and Feature Masking

Yu-Jen Chen, Xueyang Li, Yiyu Shi +1

Out-of-distribution (OOD) detection is essential for ensuring the reliability of deep learning models in medical imaging applications. This work is motivated by the observation tha…

cs.CV2024

Enhancing 3D Transformer Segmentation Model for Medical Image with Token-level Representation Learning

Xinrong Hu, Dewen Zeng, Yawen Wu +2

In the field of medical images, although various works find Swin Transformer has promising effectiveness on pixelwise dense prediction, whether pre-training these models without us…