9 citations · 9 across the 5 of their papers we have counts for
5 papers
Thyroid ultrasound diagnosis improvement via multi-view self-supervised learning and two-stage pre-training
Jian Wang, Xin Yang, Xiaohong Jia +9
Thyroid nodule classification and segmentation in ultrasound images are crucial for computer-aided diagnosis; however, they face limitations owing to insufficient labeled data. In…
Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers with Partially Annotated Ultrasound Images
Jian Wang, Liang Qiao, Shichong Zhou +6
Deep learning (DL) has proven highly effective for ultrasound-based computer-aided diagnosis (CAD) of breast cancers. In an automaticCAD system, lesion detection is critical for th…
Learning Granularity-Unified Representations for Text-to-Image Person Re-identification
Zhiyin Shao, Xinyu Zhang, Meng Fang +3
Text-to-image person re-identification (ReID) aims to search for pedestrian images of an interested identity via textual descriptions. It is challenging due to both rich intra-moda…
Flip Learning: Erase to Segment
Yuhao Huang, Xin Yang, Yuxin Zou +7
Nodule segmentation from breast ultrasound images is challenging yet essential for the diagnosis. Weakly-supervised segmentation (WSS) can help reduce time-consuming and cumbersome…
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound
Shuangchi He, Zehui Lin, Xin Yang +13
Standard plane recognition plays an important role in prenatal ultrasound (US) screening. Automatically recognizing the standard plane along with the corresponding anatomical struc…