Abstract #0098

Automatic detection and reacquisition of motion degraded images in fetal HASTE imaging at 3T

Borjan Gagoski^1,2, Junshen Xu³, Paul Wighton⁴, Dylan Tisdall⁵, Robert Frost^2,4, Sayeri Lala⁶, Wei-Ching Lo⁷, Polina Golland^8,9, Andre van der Kouwe^2,4, Elfar Adalsteinsson^8,10, and P. Ellen Grant^1,2

¹Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States, ²Department of Radiology, Harvard Medical School, Boston, MA, United States, ³(co-first author) Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁴Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ⁵Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States, ⁶Department of Electrical Engineering, Princeton University, Princeton, NJ, United States, ⁷Siemens Medical Solutions USA, Inc, Charlestown, MA, United States, ⁸Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁹Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, United States, ¹⁰Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States

Fetal brain MRI suffers from unpredictable and unconstrained fetal motion that not only causes severe image artifacts even with single-shot FSE readouts, but also results in slice-to-slice variations of the imaging plane and long scanning sessions, as the MR technologist “chases” the fetal head in an attempt to acquire artifact-free orthogonal images. In this work, we have implemented a closed-loop pipeline that automatically detects and reacquires HASTE images that were degraded by fetal motion, without any interaction from the MRI technologist. The presented methods demonstrate the basic infrastructure needed for successful prospective automated fetal brain motion correction.

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