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From the 1 of 13 linked papers with an AI index.

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20242026
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cs.CV2025

Accurate and Scalable Multimodal Pathology Retrieval via Attentive Vision-Language Alignment

Hongyi Wang, Zhengjie Zhu, Jiabo Ma +9

The rapid digitization of histopathology slides has opened up new possibilities for computational tools in clinical and research workflows. Among these, content-based slide retriev…

cs.CV2025

A Text-Image Fusion Method with Data Augmentation Capabilities for Referring Medical Image Segmentation

Shurong Chai, Rahul Kumar JAIN, Rui Xu +6

Deep learning relies heavily on data augmentation to mitigate limited data, especially in medical imaging. Recent multimodal learning integrates text and images for segmentation, k…

cs.CV2025

One Framework to Rule Them All: Unifying Multimodal Tasks with LLM Neural-Tuning

Hao Sun, Yu Song, Jiaqing Liu +3

Large-scale models have exhibited remarkable capabilities across diverse domains, including automated medical services and intelligent customer support. However, as most large mode…

cs.CV2025

EPIC: Efficient Prompt Interaction for Text-Image Classification

Xinyao Yu, Hao Sun, Zeyu Ling +5

In recent years, large-scale pre-trained multimodal models (LMMs) generally emerge to integrate the vision and language modalities, achieving considerable success in multimodal tas…

cs.CV2025

TextBraTS: Text-Guided Volumetric Brain Tumor Segmentation with Innovative Dataset Development and Fusion Module Exploration

Xiaoyu Shi, Rahul Kumar Jain, Yinhao Li +7

Deep learning has demonstrated remarkable success in medical image segmentation and computer-aided diagnosis. In particular, numerous advanced methods have achieved state-of-the-ar…

cs.CV2025

Language-guided Scale-aware MedSegmentor for Lesion Segmentation in Medical Imaging

Shuyi Ouyang, Jinyang Zhang, Xiangye Lin +4

In clinical practice, segmenting specific lesions based on the needs of physicians can significantly enhance diagnostic accuracy and treatment efficiency. However, conventional les…