Real‐time optical motion correction for diffusion tensor imaging |
| |
Authors: | Murat Aksoy Christoph Forman Matus Straka Stefan Skare Samantha Holdsworth Joachim Hornegger Roland Bammer |
| |
Affiliation: | 1. Department of Radiology, Stanford University, Stanford, California, USA;2. Pattern Recognition Lab, Department of Computer Science, Friedrich‐Alexander‐University Erlangen‐Nuremberg, Erlangen, Germany;3. Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden |
| |
Abstract: | Head motion is a fundamental problem in brain MRI. The problem is further compounded in diffusion tensor imaging because of long acquisition times, and the sensitivity of the tensor computation to even small misregistration. To combat motion artifacts in diffusion tensor imaging, a novel real‐time prospective motion correction method was introduced using an in‐bore monovision system. The system consists of a camera mounted on the head coil and a self‐encoded checkerboard marker that is attached to the patient's forehead. Our experiments showed that optical prospective motion correction is more effective at removing motion artifacts compared to image‐based retrospective motion correction. Statistical analysis revealed a significant improvement in similarity between diffusion data acquired at different time points when prospective correction was used compared to retrospective correction (P < 0.001). Magn Reson Med, 2010. © 2011 Wiley‐Liss, Inc. |
| |
Keywords: | motion DTI diffusion real‐time motion correction optical motion correction prospective motion correction |
|
|