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Abstract #4618

Segmentation of fetal pericerebral spaces based on reconstructed high-resolution MRI

Maud CAGNEAUX 1,2 , Meritxell BACH CUADRA 3,4 , Sbastien TOURBIER 3,4 , Marie SCHAER 5 , Salem HANNOUN 2 , Laurent GUIBAUD 1 , and Dominique SAPPEY-MARINIER 2

1 Radiology, Hpital Femme Mre Enfant, Lyon, France, 2 CREATIS (UMR 5220 CNRS & U1044 INSERM), University of Lyon and CERMEP-Imagerie du Vivant, Lyon, France, 3 University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 4 Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, 5 University of Geneva, Switzerland

The aim of our study is to determine the feasibility of the fetal brain segmentation applied to pericerebral spaces (PCS), which relies only on subjective pattern recognition expertise. 10 patients who underwent a fetal MRI were included. High-resolution reconstruction using motion compensation BTK was applied to obtain volumetric images of the fetal brain from 2D MR stacks. PCS were extracted using semi-automatic segmentation, requiring manual expert slice to slice corrections. Our study demonstrates the feasibility of PCS segmentation, albeit time consuming and expert-dependent. It could help diagnosing fetal cerebral pathologies and become a daily tool in the fetal brain exploration.

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