38 citations · 39 across the 5 of their papers we have counts for
9 papers · 1 filter
SAM-Driven Weakly Supervised Nodule Segmentation with Uncertainty-Aware Cross Teaching
Xingyue Zhao, Peiqi Li, Xiangde Luo +3
Automated nodule segmentation is essential for computer-assisted diagnosis in ultrasound images. Nevertheless, most existing methods depend on precise pixel-level annotations by me…
An Uncertainty-guided Tiered Self-training Framework for Active Source-free Domain Adaptation in Prostate Segmentation
Zihao Luo, Xiangde Luo, Zijun Gao +1
Deep learning models have exhibited remarkable efficacy in accurately delineating the prostate for diagnosis and treatment of prostate diseases, but challenges persist in achieving…
Ultrasound Nodule Segmentation Using Asymmetric Learning with Simple Clinical Annotation
Xingyue Zhao, Zhongyu Li, Xiangde Luo +8
Recent advances in deep learning have greatly facilitated the automated segmentation of ultrasound images, which is essential for nodule morphological analysis. Nevertheless, most…
Diversified and Personalized Multi-rater Medical Image Segmentation
Yicheng Wu, Xiangde Luo, Zhe Xu +5
Annotation ambiguity due to inherent data uncertainties such as blurred boundaries in medical scans and different observer expertise and preferences has become a major obstacle for…
3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers
Jieneng Chen, Jieru Mei, Xianhang Li +12
Medical image segmentation plays a crucial role in advancing healthcare systems for disease diagnosis and treatment planning. The u-shaped architecture, popularly known as U-Net, h…
Dual-Reference Source-Free Active Domain Adaptation for Nasopharyngeal Carcinoma Tumor Segmentation across Multiple Hospitals
Hongqiu Wang, Jian Chen, Shichen Zhang +6
Nasopharyngeal carcinoma (NPC) is a prevalent and clinically significant malignancy that predominantly impacts the head and neck area. Precise delineation of the Gross Tumor Volume…