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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