1 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
Pathological MRI Segmentation by Synthetic Pathological Data Generation in Fetuses and Neonates
Misha P. T Kaandorp, Damola Agbelese, Hosna Asma-ull +6
Developing new methods for the automated analysis of clinical fetal and neonatal MRI data is limited by the scarcity of annotated pathological datasets and privacy concerns that of…
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
Kelly Payette, Céline Steger, Roxane Licandro +64
Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and th…
Synthesis of realistic fetal MRI with conditional Generative Adversarial Networks
Marina Fernandez Garcia, Rodrigo Gonzalez Laiz, Hui Ji +2
Fetal brain magnetic resonance imaging serves as an emerging modality for prenatal counseling and diagnosis in disorders affecting the brain. Machine learning based segmentation pl…
Efficient multi-class fetal brain segmentation in high resolution MRI reconstructions with noisy labels
Kelly Payette, Raimund Kottke, Andras Jakab
Segmentation of the developing fetal brain is an important step in quantitative analyses. However, manual segmentation is a very time-consuming task which is prone to error and mus…
Longitudinal analysis of fetal MRI in patients with prenatal spina bifida repair
Kelly Payette, Ueli Moehrlen, Luca Mazzone +5
Open spina bifida (SB) is one of the most common congenital defects and can lead to impaired brain development. Emerging fetal surgery methods have shown considerable success in th…