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cs.CV2026
When to Unpair: Regulating Pairing Dependence in Medical Visual In-Context Learning
Cheng Wan, Chenjun Li, Qingyu Zhao
Visual in-context learning (ICL), well suited to label-scarce medical imaging, uses support image-label pairs to demonstrate input-output mappings, while the labels collectively in…
cs.CV2026
Unifying Active Learning and Semi-Supervised Learning for Medical Image Segmentation
Bahram Jafrasteh, Cheng Wan, Heejong Kim +2
In practical settings, medical image segmentation models are often developed with limited annotated data rather than fully labeled datasets. Training frequently begins in ultra-low…
cs.CV2026
Anatomically Guided Latent Diffusion for Brain MRI Progression Modeling
Cheng Wan, Bahram Jafrasteh, Ehsan Adeli +2
Accurately modeling longitudinal brain MRI progression is crucial for understanding neurodegenerative diseases and predicting individualized structural changes. Existing state-of-t…