Abstract #1706

Improved, rapid fetal-brain localization and orientation detection for auto-slice prescription

Malte Hoffmann^1,2, Esra Abaci Turk^3,4, Borjan Gagoski^2,3, Paul Wighton¹, M Dylan Tisdall⁵, Martin Reuter^1,2,6, Elfar Adalsteinsson^4,7, P Ellen Grant^2,3, Lawrence L Wald^1,2, and André J W van der Kouwe^1,2

¹Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, ²Department of Radiology, Harvard Medical School, Boston, MA, United States, ³Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States, ⁴Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁵Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States, ⁶German Center for Neurodegenerative Diseases, Bonn, Germany, ⁷Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States

MRI has become an invaluable tool for assessing the development of the fetal brain and can remove diagnostic doubt after routine ultrasound exams. Motion between slice prescription and acquisition, however, poses a challenge to obtaining images aligned with the standard anatomical planes, essential for evaluating morphometry. To address this, we recently presented automated slice prescription for fetal-brain MRI based on registration to a template. Here, we propose improved and fully automated fetal-brain orientation detection to advance both reliability and speed. The fast estimation is achieved by localizing the brain and eyes in an EPI scout using blob detection techniques.

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