The advent of vision foundation models, notably the Segment Anything Model (SAM), has catalyzed significant advancements in natural image segmentation. However, their direct transfer to medical imaging remains severely bottlenecked by profound domain gaps, such as cross-modality and cross-center shifts. Existing Parame...
Pretrained vision-language models (VLMs) have shown promising performance in medical image segmentation by incorporating clinical text. However, it remains unclear how much textual information actually contributes to pixel-level predictions. In this work, we systematically investigate the role of text in multimodal med...
In industrial computed tomography for defect detection in 18650 lithium-ion batteries, streak-like artifacts caused by sparse-view projection sampling severely hinder the accurate identification of subtle structural defects. This paper proposes a hybrid-domain CT reconstruction algorithm with projection inpainting base...
Zihao Liu, Chenglong Wang, Zhengxin Li et al.· International Conference on...· 0 citations
Accurate segmentation of polyps and skin lesions is pivotal for clinical diagnosis, yet existing methods struggle with low contrast, ambiguous boundaries, and cross-domain distribution discrepancies. Discriminative networks and most diffusion-based segmentation approaches predict standalone binary masks, leaving the vi...
Zihao Liu, Zhe Zhu, Xuzi Shi· 0 citations
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