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20232026
most citedCross-modality Attention Adapter: A Glioma Segmentation Fine-tuning Method for SAM Using Multimodal Brain MR Images

7 citations · 11 across the 13 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

SemSim: Revisiting Weak-to-Strong Consistency from a Semantic Similarity Perspective for Semi-supervised Medical Image Segmentation

Shiao Xie, Hongyi Wang, Ziwei Niu +4

Semi-supervised learning (SSL) for medical image segmentation is a challenging yet highly practical task, which reduces reliance on large-scale labeled dataset by leveraging unlabe…

cs.CV2024

M2OST: Many-to-one Regression for Predicting Spatial Transcriptomics from Digital Pathology Images

Hongyi Wang, Xiuju Du, Jing Liu +3

The advancement of Spatial Transcriptomics (ST) has facilitated the spatially-aware profiling of gene expressions based on histopathology images. Although ST data offers valuable i…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 1 cited

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.MM2024

Multimodal Infusion Tuning for Large Models

Hao Sun, Yu Song, Xinyao Yu +3

Recent advancements in large-scale models have showcased remarkable generalization capabilities in various tasks. However, integrating multimodal processing into these models prese…