IUGC: A benchmark of landmark detection in end-to-end intrapartum ultrasound biometry
Year: 2026
Type: article
Source: Medical Image Analysis
Authors: Jieyun Bai, Yitong Tang, Xiao Liu, Jiale Hu, Yunda Li, Xufan Chen, Yufeng Wang, Chen Ma, Yunshu Li, Bowen Guo, Jing Jiao, Yi Huang, Kun Wang, Lifei Li, Yuzhang Ma, Xiaoxin Han, Haochen Shao, Zi Yang, Qingchen Liu, Yuchen Hu, Jingfan Kuang, Shanglin Song, Anirvan Krishna, Zaid Ahmed Khan, Zelan Li, Zhengyang Zhang, Hansen Zhang, Yan Cheng, Xuezhi Zhang, Xi Chen, Hao Yan, Lyuyang Tong, Bo Du, Bo Deng, Yu Chen, Zilun Peng, Saeid Rezaei, Jie Gan, Weidong Cai, Fangyijie Wang, Kathleen M. Curran, Guénolé Silvestre, Isaac Khobo, Yaosheng Lu, Dong Ni, Yuxin Huang, Mohammad Yaqub, Jun Ma, Karim Lekadir, Shuo Li
Institutions: University of Auckland, Jinan University, First Affiliated Hospital of Jinan University, Nanyang Institute of Technology, Fudan University, Wuhan University, Zhujiang Hospital, Southern Medical University, Gansu University of Traditional Chinese Medicine, First Hospital of Lanzhou University, Lanzhou University, Indian Institute of Technology Kharagpur, Northeastern University, University College Cork, The University of Sydney, University College Dublin, University of Cape Town, Shenzhen University, Mohamed bin Zayed University of Artificial Intelligence, University Health Network, Case Western Reserve University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: closed
Funders: National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province, China Scholarship Council, Guangzhou Municipal Science and Technology Bureau, HORIZON EUROPE Framework Programme, European Research Council, Guangzhou Municipal Science and Technology Project, Key Technologies Research and Development Program of Guangzhou, Guangxi Key Research and Development Program, High-end Foreign Experts Recruitment Plan of China
OpenAlex ID: W7125518023