3 papers
cs.CV2026
MIND: Multimodal Intent-Driven Network via Diffusion Transformers for Medical Image Fusion
Yunzhan Fu, Xiangyu Shen, Yifei Sun +3
The paper introduces MIND, a network that uses diffusion transformers guided by intent-driven text generated from BioMedGPT to fuse medical images while preserving pathology-aware…
cs.CV2026
SCALPEL: Semantic Cross-modal Alignment via LLM-Powered Encoder Learning for Medical Vision-Language Representation
Yunzhan Fu, Enyu Bao, Xiangyu Shen +4
The paper introduces SCALPEL, a framework that fine‑tunes a generative medical LLM into an isotropic encoder and uses an asymmetric, anatomy‑negation‑aware contrastive objective to…
cs.CV2026
SemiSAM-O1: Pushing the Boundary of Annotation-Efficient Medical Image Segmentation with Generalist Knowledge Fusion
Yichi Zhang, Le Xue, Bichun Xu +6
Semi-supervised learning (SSL) has become a promising solution to alleviate the annotation burden of deep learning-based medical image segmentation models. While recent advances in…