63 citations · 86 across the 5 of their papers we have counts for
5 papers
A multi-centre, multi-device benchmark dataset for landmark-based comprehensive fetal biometry
Chiara Di Vece, Zhehua Mao, Netanell Avisdris +7
Accurate fetal growth assessment from ultrasound (US) relies on precise biometry measured by manually identifying anatomical landmarks in standard planes. Manual landmarking is tim…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
Automatic fetal fat quantification from MRI
Netanell Avisdris, Aviad Rabinowich, Daniel Fridkin +9
Normal fetal adipose tissue (AT) development is essential for perinatal well-being. AT, or simply fat, stores energy in the form of lipids. Malnourishment may result in excessive o…
BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes
Netanell Avisdris, Leo Joskowicz, Brian Dromey +5
Fetal growth assessment from ultrasound is based on a few biometric measurements that are performed manually and assessed relative to the expected gestational age. Reliable biometr…
Fetal Brain Tissue Annotation and Segmentation Challenge Results
Kelly Payette, Hongwei Li, Priscille de Dumast +55
In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital ste…