activity
20202022
most citedMulti-dimensional topological loss for cortical plate segmentation in fetal brain MRI

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV2022

Domain generalization in fetal brain MRI segmentation \\with multi-reconstruction augmentation

Priscille de Dumast, Meritxell Bach Cuadra

Quantitative analysis of in utero human brain development is crucial for abnormal characterization. Magnetic resonance image (MRI) segmentation is therefore an asset for quantitati…

eess.IV2022★ 2 cited

Multi-dimensional topological loss for cortical plate segmentation in fetal brain MRI

Priscille de Dumast, Hamza Kebiri, Vincent Dunet +2

The fetal cortical plate (CP) undergoes drastic morphological changes during the in utero development. Therefore, CP growth and folding patterns are key indicator in the assessment…

eess.IV2021★ 1 cited

Synthetic magnetic resonance images for domain adaptation: Application to fetal brain tissue segmentation

Priscille de Dumast, Hamza Kebiri, Kelly Payette +3

The quantitative assessment of the developing human brain in utero is crucial to fully understand neurodevelopment. Thus, automated multi-tissue fetal brain segmentation algorithms…

eess.IV2020

Segmentation of the cortical plate in fetal brain MRI with a topological loss

Priscille de Dumast, Hamza Kebiri, Chirine Atat +3

The fetal cortical plate undergoes drastic morphological changes throughout early in utero development that can be observed using magnetic resonance (MR) imaging. An accurate MR im…

eess.IV2020

An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset

Kelly Payette, Priscille de Dumast, Hamza Kebiri +17

It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders.…