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From the 1 of 12 linked papers with an AI index.

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20242026
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12 papers

cs.CV2026

Shared Semantic Codebook Distillation for Unpaired Cross-Modal Medical Classification

Dillan Imans, Phuoc-Nguyen Bui, Duc-Tai Le +1

The paper introduces Shared Semantic Codebook Distillation, a method that transfers diagnostic knowledge between unpaired medical imaging modalities by representing images with a c…

cs.CV2026

Response-Aware Multimodal Learning for Post-Treatment Visual Acuity Forecasting

Phuoc-Nguyen Bui, Van-Vi Vo, Duc-Tai Le +5

Long-term visual acuity (VA) outcomes after anti-VEGF therapy are central to patient counseling, expectation setting, and follow-up planning in diabetic macular edema (DME). Howeve…

cs.CV2026

Frequency Adapter with SAM for Generalized Medical Image Segmentation

Phuoc-Nguyen Bui, Van-Nguyen Pham, Duc-Tai Le +2

Medical image segmentation is a critical task in computer-aided diagnosis and treatment planning. However, deep learning models often struggle to generalize across datasets due to…

cs.CV2026

Representation Learning with Semantic-aware Instance and Sparse Token Alignments

Phuoc-Nguyen Bui, Toan Duc Nguyen, Junghyun Bum +2

Medical contrastive vision-language pre-training (VLP) has demonstrated significant potential in improving performance on downstream tasks. Traditional approaches typically employ…

cs.CV2026

Clinical Graph-Mediated Distillation for Unpaired MRI-to-CFI Hypertension Prediction

Dillan Imans, Phuoc-Nguyen Bui, Duc-Tai Le +1

Retinal fundus imaging enables low-cost and scalable hypertension (HTN) screening, but HTN-related retinal cues are subtle, yielding high-variance predictions. Brain MRI provides s…

cs.CV2026

Unsupervised Domain Adaptation with SAM-RefiSeR for Enhanced Brain Tumor Segmentation

Dillan Imans, Phuoc-Nguyen Bui, Duc-Tai Le +1

Unsupervised Domain Adaptation with SAM-RefiSeR for Enhanced Brain Tumor Segmentation