Most existing artificial intelligence systems for breast ultrasound rely primarily on image-driven prediction, with limited incorporation of the knowledge from the Breast Imaging Reporting and Data System (BI-RADS) and the intermediate assessment processes underlying radiologists'workflow, thereby constraining their in...
Sheng-Zhou Zhong, Zi-Yi Wang, Lian-Fu Li et al.· 0 citations
A novel 3D UXFormer model is introduced that combines the 3D UNET and Vision Transformer (ViT) through a dual-branch structure, capitalizing on the 3D UNET's local feature extraction prowess and ViT's global feature-capturing ability.
Xiao-Dong Zheng, Zhi-Tao Wei, Si-Yao Du et al.· Interdisciplinary Sciences C...· 0 citations
Segmenting breast tumors in magnetic resonance imaging (MRI) is a critical step in computer-aided diagnosis. Recently, the Segment Anything Model (SAM) has demonstrated remarkable potential in medical image segmentation. However, the immense parameter size and heavy computational burden of SAM's Transformer-based archi...
Xiang-Bin Luo, Chuan-Song Fan, Zhen-Wei Shi et al.· Conference on Advanced Algor...· 0 citations
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