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Abstract #3667

Non Rigid-Body Motion Detection Using Single 6-DOF Data From Skin Based Markers for Brain Imaging

Aditya Singh 1 , Brian Keating 1 , Benjamin Zahneisen 1 , Michael Herbst 1 , and Thomas Ernst 1

1 John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii, United States

Prospective motion correction for brain MRI using external tracking systems with skin-attached markers may suffer from errors in head tracking data introduced by changes in facial expressions, such as squinting. We demonstrate the feasibility of detecting non rigid-body motion events using single 6-DOF information, with an algorithm that is validated on motion data obtained from a trained volunteer and seven clinical subjects who performed involuntary motion. The receiver operation characteristic of the algorithm was calculated to show a mean false positive rate of 0.09, true positive rate of 0.38 and a positive predictive value of 0.86.

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