Abstract #3892

A pre-processing pipeline for bias field correction and rigid and elastic motion compensation in Placental-Fetal BOLD MRI

Esra Abaci Turk^1,2, Jie Luo^1,2, Borjan Gagoski ¹, Carolina Bibbo³, Julian N. Robinson³, P. Ellen Grant¹, Elfar Adalsteinsson^2,4,5, Polina Golland^4,6, and Norberto Malpica^2,7

¹Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States, ²Madrid-MIT M+Vision Consortium in RLE, Massachusetts Institute of Technology, Cambridge, MA, United States, ³Maternal and Fetal Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States, ⁴Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁵Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁶Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, United States, ⁷Medical Image Analysis and Biometry Laboratory, Universidad Rey Juan Carlos, Madrid, Spain

Abnormal oxygen transport through the placenta is thought to be a major etiologic factor in intrauterine growth restriction (IUGR). Blood-oxygen-level-dependent (BOLD) magnetic resonance imaging (MRI) with oxygen exposure is a non-invasive technique that can estimate oxygenation changes in specific organs. However, applying this technique to placentae and fetal organs can be challenging due to non-uniform signal and unpredictable fetal and maternal motion. This study presents a preprocessing pipeline to mitigate signal non-uniformities and motion, to enable automated regional analysis of placenta and fetal body for BOLD MRI studies.

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