44 citations · 186 across the 25 of their papers we have counts for
6 papers · 2 filters
Masked Diffusion as Self-supervised Representation Learner
Zixuan Pan, Jianxu Chen, Yiyu Shi
Denoising diffusion probabilistic models have recently demonstrated state-of-the-art generative performance and have been used as strong pixel-level representation learners. This p…
Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis
Ching-Hao Chiu, Hao-Wei Chung, Yu-Jen Chen +2
Fairness has become increasingly pivotal in medical image recognition. However, without mitigating bias, deploying unfair medical AI systems could harm the interests of underprivil…
How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Images
Xinrong Hu, Xiaowei Xu, Yiyu Shi
The emerging scale segmentation model, Segment Anything (SAM), exhibits impressive capabilities in zero-shot segmentation for natural images. However, when applied to medical image…
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain Tumor
Yu-Jen Chen, Xinrong Hu, Yiyu Shi +1
Magnetic resonance imaging (MRI) is commonly used for brain tumor segmentation, which is critical for patient evaluation and treatment planning. To reduce the labor and expertise r…
A Novel Confidence Induced Class Activation Mapping for MRI Brain Tumor Segmentation
Yu-Jen Chen, Yiyu Shi, Tsung-Yi Ho
Magnetic resonance imaging (MRI) is a commonly used technique for brain tumor segmentation, which is critical for evaluating patients and planning treatment. To make the labeling p…
Multimodal Understanding Through Correlation Maximization and Minimization
Yifeng Shi, Marc Niethammer
Multimodal learning has mainly focused on learning large models on, and fusing feature representations from, different modalities for better performances on downstream tasks. In th…