Recent advances in large-scale foundation models have enabled strong generalization across a wide range of clinical and research tasks in magnetic resonance imaging (MRI). However, existing vision-language MRI models remain limited in anatomy-specific localization and pathology-aware representation, particularly in rea...
Noel DSouza, Zhi-Jian Yang, Nishank Singla et al.· 0 citations
Salient-Q, a saliency-guided vision-language framework that addresses challenges of PHI identification and localization through three architectural innovations, outperforms other baseline models in terms of PHI identification and localization.
Sicheng Zhou, Zai-Fu Zhan, Lei Wu et al.· Proceedings of the 32nd ACM...· 0 citations
DenseAR is extended to a unified model that handles multiple modalities and imaging tasks within a single backbone that unifies cross-modal translation, modality-conditioned generation, and tumor segmentation, while remaining competitive with task-specific methods.
Chicago Y. Park, Jia-Lin Mao, Xiaojian Xu et al.· arXiv.org· 0 citations
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