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Abstract #0297

Prediction of Motion Induced Image Degradation Using a Markerless Motion Tracker

Rasmus Munch Olsen1, Helle Hjorth Johannesen2, Otto Mølby Henriksen2, Lisbeth Marner2, and Oline Vinter Olesen1,2,3

1DTU Compute, Technical University of Denmark, Lyngby, Denmark, 2Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark, 3TracInnovations, Ballerup, Denmark

In this work a markerless motion tracker, TCL2, is used to predict image quality in 3D T1 weighted MPRAGE MRI brain scans. An experienced radiologist scored the image quality for 172 scans as being usable or not usable, i.e. if a repeated scan was required. Based on five motion parameters, a classification algorithm was trained and an accuracy for identifying not usable images of 95.9% was obtained with a sensitivity of 91.7% and specificity of 96.3%. This work shows the feasibility of the markerless motion tracker for predicting image quality with a high accuracy.

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