Distortion correction and robust tensor estimation for MR diffusion imaging

Distortion correction and robust tensor estimation for MR diffusion imaging. Mangin, J., Poupon, C., Clark, C., Le Bihan, D., & Bloch, I. Medical Image Analysis, 6(3):191–198, 2002.

Paper doi abstract bibtex

This paper presents a new procedure to estimate the diffusion tensor from a sequence of diffusion-weighted images. The first step of this procedure consists of the correction of the distortions usually induced by eddy-current related to the large diffusion-sensitizing gradients. This correction algorithm relies on the maximization of mutual information to estimate the three parameters of a geometric distortion model inferred from the acquisition principle. The second step of the procedure amounts to replacing the standard least squares-based approach by the Geman-McLure M-estimator, in order to reduce outlier-related artefacts. Several experiments prove that the whole procedure highly improves the quality of the final diffusion maps.

@article{mangin_distortion_2002,
	title = {Distortion correction and robust tensor estimation for {MR} diffusion imaging},
	volume = {6},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12270226},
	doi = {10/fpm9tz},
	abstract = {This paper presents a new procedure to estimate the diffusion tensor from a sequence of diffusion-weighted images. The first step of this procedure consists of the correction of the distortions usually induced by eddy-current related to the large diffusion-sensitizing gradients. This correction algorithm relies on the maximization of mutual information to estimate the three parameters of a geometric distortion model inferred from the acquisition principle. The second step of the procedure amounts to replacing the standard least squares-based approach by the Geman-McLure M-estimator, in order to reduce outlier-related artefacts. Several experiments prove that the whole procedure highly improves the quality of the final diffusion maps.},
	number = {3},
	journal = {Medical Image Analysis},
	author = {Mangin, J.F. and Poupon, C. and Clark, C. and Le Bihan, D. and Bloch, I.},
	year = {2002},
	keywords = {\#nosource, *Artifacts Brain/*anatomy \& histology Diffusion Magnetic Resonance Imaging/*methods Humans Image Enhancement/*methods *Models, Statistical Quality Control Reproducibility of Results Sensitivity and Specificity Statistics Stochastic Processes},
	pages = {191--198},
}

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