Conference paper
Prediction of Motion Induced Image Degradation Using a Markerless Motion Tracker
Department of Electrical Engineering, Technical University of Denmark1
Biomedical Engineering, Department of Electrical Engineering, Technical University of Denmark2
Copenhagen University Hospital Herlev and Gentofte3
Department of Applied Mathematics and Computer Science, Technical University of Denmark4
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark5
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.
| Language: | English |
|---|---|
| Year: | 2017 |
| Proceedings: | ISMRM 25th Annual Meeting & Exhibition |
| Types: | Conference paper |
| ORCIDs: | Olesen, Oline Vinter |
