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Proceedings Paper

Reconstruction of a geometrically correct diffusion tensor image of a moving human fetal brain
Author(s): Kio Kim; Piotr A. Habas; Francois Rousseau; Orit A. Glenn; A. James Barkovich; Meriam Koob; Jean-Louis Dietemann; Ashley J. Robinson; Kenneth J. Poskitt; Steven P. Miller; Colin Studholme
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Paper Abstract

Recent studies reported the development of methods for rigid registration of 2D fetal brain imaging data to correct for unconstrained fetal and maternal motion, and allow the formation of a true 3D image of conventional fetal brain anatomy from conventional MRI. Diffusion tensor imaging provides additional valuable insight into the developing brain anatomy, however the correction of motion artifacts in clinical fetal diffusion imaging is still a challenging problem. This is due to the challenging problem of matching lower signal-to-noise ratio diffusion weighted EPI slice data to recover between-slice motion, compounded by the presence of possible geometric distortions in the EPI data. In addition, the problem of estimating a diffusion model (such as a tensor) on a regular grid that takes into account the inconsistent spatial and orientation sampling of the diffusion measurements needs to be solved in a robust way. Previous methods have used slice to volume registration within the diffusion dataset. In this work, we describe an alternative approach that makes use of an alignment of diffusion weighted EPI slices to a conventional structural MRI scan which provides a geometrically correct reference image. After spatial realignment of each diffusion slice, a tensor field representing the diffusion profile is estimated by weighted least squared fitting. By qualitative and quantitative evaluation of the results, we confirm the proposed algorithm successfully corrects the motion and reconstructs the diffusion tensor field.

Paper Details

Date Published: 13 March 2010
PDF: 9 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76231I (13 March 2010); doi: 10.1117/12.844542
Show Author Affiliations
Kio Kim, Univ. of California, San Francisco (United States)
Piotr A. Habas, Univ. of California, San Francisco (United States)
Francois Rousseau, LSIIT, CNRS, Univ. of Strasbourg (France)
Orit A. Glenn, Univ. of California, San Francisco (United States)
A. James Barkovich, Univ. of California, San Francisco (United States)
Meriam Koob, LINC, CNRS, Univ. of Strasbourg (France)
Jean-Louis Dietemann, LINC, CNRS, Univ. of Strasbourg (France)
Ashley J. Robinson, Univ. of British Columbia (Canada)
Kenneth J. Poskitt, Univ. of British Columbia (Canada)
Steven P. Miller, Univ. of California, San Francisco (United States)
Univ. of British Columbia (Canada)
Colin Studholme, Univ. of California, San Francisco (United States)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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