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Proceedings Paper

Quantitative assessment of mis-registration issues of diffusion tensor imaging (DTI)
Author(s): Yue Li; Hangyi Jiang; Susumu Mori
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Paper Abstract

Image distortions caused by eddy current and patient motion have been two major sources of the mis-registration issues in diffusion tensor imaging (DTI). Numerous registration methods have been proposed to correct them. However, quality control of DTI remains an important issue, because we rarely report how much mis-registration existed and how well they were corrected. In this paper, we propose a method for quantitative reporting of DTI data quality. This registration method minimizes a cost function based on mean square tensor fitting errors. Registration with twelve-parameter full affine transformation is used. From the registration result, distortion and motion parameters are estimated. Because the translation parameters involve both eddy-current-induced image translation and the patient motion, by analyzing the transformation model, we separate them by removing the contributions that are linearly correlated with diffusion gradients. We define the metrics measuring the amounts of distortion, rotation, translation. We tested our method on a database with 64 subjects and found the statistics of each of metrics. Finally we demonstrate that how these statistics can be used for assessing the data quality quantitatively in several examples.

Paper Details

Date Published: 14 February 2012
PDF: 8 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83141Y (14 February 2012); doi: 10.1117/12.911129
Show Author Affiliations
Yue Li, The Johns Hopkins Univ. School of Medicine (United States)
Hangyi Jiang, The Johns Hopkins Univ. School of Medicine (United States)
Susumu Mori, The Johns Hopkins Univ. School of Medicine (United States)

Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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