Area of research
Pediatrics, Perinatology and Child Health · Surgery
Research interest
Research interests include Computer science, Artificial intelligence, Segmentation, Convolutional neural network, Medicine, and Image segmentation.
A Dempster-Shafer Approach to Trustworthy AI With Application to Fetal Brain MRI Segmentation
Fetal brain tissue annotation and segmentation challenge results
Abnormal fetal ultrasound leading to the diagnosis of ADNP syndrome
MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning
<scp>MRI</scp> Characteristics of Pediatric Renal Tumors: A <scp>SIOP‐RTSG</scp> Radiology Panel Delphi Study
Label-Set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation
Fetal endoscopic tracheal occlusion reverses the natural history of right‐sided congenital diaphragmatic hernia: European multicenter experience
Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI
Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning
DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation
An Automated Localization, Segmentation and Reconstruction Framework for Fetal Brain MRI
Reliability of MR Imaging–Based Posterior Fossa and Brain Stem Measurements in Open Spinal Dysraphism in the Era of Fetal Surgery
Slic-Seg: A minimally interactive segmentation of the placenta from sparse and motion-corrupted fetal MRI in multiple views
GIFT-Cloud: A data sharing and collaboration platform for medical imaging research