Beyond benchmarks of IUGC: Rethinking requirements of deep learning method for intrapartum ultrasound biometry from fetal ultrasound videos
- Jieyun Bai
- , Zihao Zhou
- , Yitong Tang
- , Jie Gan
- , Zhuonan Liang
- , Jianan Fan
- , Lisa B. Mcguire
- , Jillian L. Clarke
- , Weidong Cai
- , Jacaueline Spurway
- , Yubo Tan
- , Shiye Wang
- , Wenda Shen
- , Wangwang Yu
- , Yihao Li
- , Philippe Zhang
- , Weili Jiang
- , Yongjie Li
- , Salem Muhsin Ali Binqahal Al Nasi
- , Arsen Abzhanov
- The First Affiliated Hospital of Jinan University
- The University of Auckland
- The University of Sydney
- University of Sydney
- Medical Imaging
- University of Electronic Science and Technology of China
- Henan Kaifeng College of Science Technology and Communication
- Changchun University of Science and Technology
- United Imaging Healthcare
- IUEM / LOPS / Université de Bretagne Occidentale
- Sichuan University
- University of Artificial Intelligence
- Chongqing Institute of Technology
- University of Oxford
- Nanyang Technological University
- Shanghai Jiao Tong University
- Chongqing Normal University
- University of Manchester
- Southwest University
- German Cancer Research Center
- Hong Kong University of Science and Technology
- Ibn Rochd university-hospital center-Casablanca
- University of Barcelona
- University of Cape Town
- Southern Medical University
- Third Affiliated Hospital of Sun Yat-sen University
- for Child Health
- King Abdullah University of Science and Technology
- Shenzhen University
- Catalan Institution for Research and Advanced Studies (ICREA)
- Department of Biomedical Engineering
Research output: Contribution to journal › Short survey › peer-review
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Citation
(Scopus)