5 citations · 14 across the 6 of their papers we have counts for
11 papers
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…
Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound
Xin Yang, Yuhao Huang, Ruobing Huang +10
3D ultrasound (US) has become prevalent due to its rich spatial and diagnostic information not contained in 2D US. Moreover, 3D US can contain multiple standard planes (SPs) in one…
Agent with Warm Start and Adaptive Dynamic Termination for Plane Localization in 3D Ultrasound
Xin Yang, Haoran Dou, Ruobing Huang +9
Accurate standard plane (SP) localization is the fundamental step for prenatal ultrasound (US) diagnosis. Typically, dozens of US SPs are collected to determine the clinical diagno…
Contrastive Rendering for Ultrasound Image Segmentation
Haoming Li, Xin Yang, Jiamin Liang +12
Ultrasound (US) image segmentation embraced its significant improvement in deep learning era. However, the lack of sharp boundaries in US images still remains an inherent challenge…
Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound
Yuhao Huang, Xin Yang, Rui Li +10
3D ultrasound (US) is widely used due to its rich diagnostic information, portability and low cost. Automated standard plane (SP) localization in US volume not only improves effici…
Hybrid Attention for Automatic Segmentation of Whole Fetal Head in Prenatal Ultrasound Volumes
Xin Yang, Xu Wang, Yi Wang +6
Background and Objective: Biometric measurements of fetal head are important indicators for maternal and fetal health monitoring during pregnancy. 3D ultrasound (US) has unique adv…