Motion Detection in Diffusion MRI via Online ODF Estimation. (21st February 2013)

• Record Type: Journal Article
• Authors: Caruyer, Emmanuel; Aganj, Iman; Lenglet, Christophe; Sapiro, Guillermo; Deriche, Rachid
• Other Names: Zhuang Tiange Academic Editor.
• Is Part Of: International journal of biomedical imaging. Volume 2013(2013)
• Publication Date: 2013-02-21
• Subjects: Diagnostic imaging -- Periodicals; Imaging systems in medicine -- Periodicals; Imagerie pour le diagnostic; Imagerie médicale; Diagnostic imaging; Imaging systems in medicine; Diagnostic Imaging -- Periodicals; Electronic journals; Periodicals; 616.0754
• DOI: 10.1155/2013/849363
• Languages: English
• ISSNs: 1687-4188

Abstract

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.