Improving cross-domain brain tissue segmentation in fetal MRI with synthetic data

arXiv:2403.15103v1 Announce Type: cross
Abstract: Segmentation of fetal brain tissue from magnetic resonance imaging (MRI) plays a crucial role in the study of in utero neurodevelopment. However, automated tools face substantial domain shift challenges as they must be robust to highly heterogeneous clinical data, often limited in numbers and lacking annotations. Indeed, high variability of the fetal brain morphology, MRI acquisition parameters, and superresolution reconstruction (SR) algorithms adversely affect the model's performance when evaluated out-of-domain. In this work, we introduce …

abstract arxiv automated brain challenges clinical cs.cv cs.lg data domain eess.iv face however imaging improving mri numbers robust role segmentation shift study synthetic synthetic data tools type