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Abstract #0713

Continuous 4D atlas of normal fetal lung development and automated CNN-based lung volumetry for motion-corrected fetal body MRI 

Alena Uus1, Irina Grigorescu1, Aditi Shetty1, Alexia Egloff Collado2, Joseph Davidson3,4, Milou van Poppel1,5, Johannes Steinweg2, Lisa Story2, Michael Aertsen6,7, Jan Deprest8, Jim Carmichael9, Joseph V Hajnal1,2, Mary Rutherford2, and Maria Deprez1
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 3Prenatal Cell and Gene Therapy, Elizabeth Garrett Anderson Institute of Women’s Health, University College London, London, United Kingdom, 4Stem Cells and Regenerative Medicine, GOS-UCL Institute of Child Health, London, United Kingdom, 5Department of Congenital Heart Disease, Evelina Children’s Hospital, London, United Kingdom, 6Department of Radiology, University Hospitals Leuven, Leuven, Belgium, 7Department of Imaging and Pathology, Biomedical Sciences, KU Leuven, Leuven, Belgium, 8Department of Obstetrics, University Hospitals KU Leuven, Leuven, Belgium, 9Paediatric Radiology, Evelina London Children’s Hospital, London, United Kingdom

This work presents a continuous 4D atlas of fetal lung development within 22-32 weeks gestational age (GA) generated from ~130 motion-corrected fetal body MRI datasets. The corresponding growth charts for fetal MRI lung indices are used for definition of the of normal ranges. In addition, we implemented and evaluated an automated method for fetal lung volumetry based on 3D UNet segmentations.

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