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      Motion Detection in Diffusion MRI via Online ODF Estimation

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          Abstract

          The acquisition of high angular resolution diffusion MRI is particularly long and subject motion can become an issue. The orientation distribution function (ODF) can be reconstructed online incrementally from diffusion-weighted MRI with a Kalman filtering framework. This online reconstruction provides real-time feedback throughout the acquisition process. In this article, the Kalman filter is first adapted to the reconstruction of the ODF in constant solid angle. Then, a method called STAR (STatistical Analysis of Residuals) is presented and applied to the online detection of motion in high angular resolution diffusion images. Compared to existing techniques, this method is image based and is built on top of a Kalman filter. Therefore, it introduces no additional scan time and does not require additional hardware. The performance of STAR is tested on simulated and real data and compared to the classical generalized likelihood ratio test. Successful detection of small motion is reported (rotation under 2°) with no delay and robustness to noise.

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          Age-related decline in brain white matter anisotropy measured with spatially corrected echo-planar diffusion tensor imaging.

          Adrienne Sullivan, M Hedehus, M. Moseley … (2000)
          Echo planar (EP) diffusion tensor imaging (DTI) permits in vivo identification of the orientation and coherence of brain white matter tracts but suffers from field inhomogeneity-induced geometric distortion. To reduce spatial distortion, polynomial warping corrections were applied and the effects tested on measures of fractional anisotropy (FA) in the genu and splenium of corpus callosum. Implementation entailed spatially warping EP images obtained without diffusion weighting (b = 0) to long-echo T(2)-weighted fast spin echo images, collected for anatomical delineation, tissue segmentation, and coregistration with the diffusion images. Using the optimal warping procedure (third-order polynomial), the effects of age on FA and a quantitative measure of intervoxel coherence (C) in the genu, splenium, centrum semiovale, and frontal and parietal pericallosal white matter were examined in 31 healthy men (23-76 years). FA declined significantly with age in all regions except the splenium, whereas intervoxel coherence positively correlated with age in the genu. Magn Reson Med 44:259-268, 2000. Copyright 2000 Wiley-Liss, Inc.
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            Principles of nuclear magnetic resonance microscopy

            PT Callaghan, Paul T. Callaghan, P. Callaghan … (1993)
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              Diffusion imaging with prospective motion correction and reacquisition.

              Christine Benner, W. Van Den Wollenberg, Charlotte Sørensen (2011)
              A major source of artifacts in diffusion-weighted imaging is subject motion. Slow bulk subject motion causes misalignment of data when more than one average or diffusion gradient direction is acquired. Fast bulk subject motion can cause signal dropout artifacts in diffusion-weighted images and results in erroneous derived maps, e.g., fractional anisotropy maps. To address both types of artifacts, a fully automatic method is presented that combines prospective motion correction with a reacquisition scheme. Motion correction is based on the prospective acquisition correction method modified to work with diffusion-weighted data. The images to reacquire are determined automatically during the acquisition from the imaging data, i.e., no extra reference scan, navigators, or external devices are necessary. The number of reacquired images, i.e., the additional scan duration can be adjusted freely. Diffusion-weighted prospective acquisition correction corrects slow bulk motion well and reduces misalignment artifacts like image blurring. Mean absolute residual values for translation and rotation were <0.6 mm and 0.5°. Reacquisition of images affected by signal dropout artifacts results in diffusion maps and fiber tracking free of artifacts. The presented method allows the reduction of two types of common motion related artifacts at the cost of slightly increased acquisition time. Copyright © 2011 Wiley-Liss, Inc.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Int J Biomed Imaging
                Journal ID (iso-abbrev): Int J Biomed Imaging
                Journal ID (publisher-id): IJBI
                Title: International Journal of Biomedical Imaging
                Publisher: Hindawi Publishing Corporation
                ISSN (Print): 1687-4188
                ISSN (Electronic): 1687-4196
                Publication date (Print): 2013
                Publication date (Electronic): 21 February 2013
                Volume: 2013
                Electronic Location Identifier: 849363
                Affiliations
                1Athena Project-Team, INRIA, 2004 Route des Lucioles, BP93, 06902 Sophia Antipolis, INRIA Sophia Antipolis Méditerranée, France
                2Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Harvard Medical School, 149 13th Street, Charlestown, MA 02129, USA
                3LIDS, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 32-D608, Cambridge, MA 02139, USA
                4Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, 2021 Sixth Street SE, Minneapolis, MN 55455, USA
                5Department of Electrical and Computer Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, MN 55455, USA
                Author notes

                Academic Editor: Tiange Zhuang

                Article
                DOI: 10.1155/2013/849363
                PMC ID: 3594974
                PubMed ID: 23509445
                SO-VID: 78b45133-7422-45c8-a61d-01315ce903ff
                Copyright © Copyright © 2013 Emmanuel Caruyer et al.
                License:

                This is an open access paper distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 15 June 2012
                Date revision received : 31 December 2012
                Date accepted : 4 January 2013
                Categories
                Subject: Research Article

                ScienceOpen disciplines: Radiology & Imaging
                Data availability:
                ScienceOpen disciplines: Radiology & Imaging

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