Quantification of measurement error in DTI: Theoretical predictions and validation

Casey Goodlett; P. Thomas Fletcher; Weili Lin; Guido Gerig

doi:10.1007/978-3-540-75757-3_2

Quantification of measurement error in DTI: Theoretical predictions and validation

Casey Goodlett, P. Thomas Fletcher, Weili Lin, Guido Gerig

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The presence of Rician noise in magnetic resonance imaging (MRI) introduces systematic errors in diffusion tensor imaging (DTI) measurements. This paper evaluates gradient direction schemes and tensor estimation routines to determine how to achieve the maximum accuracy and precision of tensor derived measures for a fixed amount of scan time. We present Monte Carlo simulations that quantify the effect of noise on diffusion measurements and validate these simulation results against appropriate in-vivo images. The predicted values of the systematic and random error caused by imaging noise are essential both for interpreting the results of statistical analysis and for selecting optimal imaging protocols given scan time limitations.

Original language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings
Publisher	Springer Verlag
Pages	10-17
Number of pages	8
Edition	PART 1
ISBN (Print)	9783540757566
DOIs	https://doi.org/10.1007/978-3-540-75757-3_2
State	Published - 2007
Event	10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007 - Brisbane, Australia Duration: Oct 29 2007 → Nov 2 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	4791 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007
Country/Territory	Australia
City	Brisbane
Period	10/29/07 → 11/2/07

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-75757-3_2

Cite this

Goodlett, C., Fletcher, P. T., Lin, W., & Gerig, G. (2007). Quantification of measurement error in DTI: Theoretical predictions and validation. In Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings (PART 1 ed., pp. 10-17). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4791 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-75757-3_2

Quantification of measurement error in DTI: Theoretical predictions and validation. / Goodlett, Casey; Fletcher, P. Thomas; Lin, Weili et al.
Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings. PART 1. ed. Springer Verlag, 2007. p. 10-17 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4791 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Goodlett, C, Fletcher, PT, Lin, W & Gerig, G 2007, Quantification of measurement error in DTI: Theoretical predictions and validation. in Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4791 LNCS, Springer Verlag, pp. 10-17, 10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007, Brisbane, Australia, 10/29/07. https://doi.org/10.1007/978-3-540-75757-3_2

Goodlett C, Fletcher PT, Lin W, Gerig G. Quantification of measurement error in DTI: Theoretical predictions and validation. In Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings. PART 1 ed. Springer Verlag. 2007. p. 10-17. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-75757-3_2

Goodlett, Casey ; Fletcher, P. Thomas ; Lin, Weili et al. / Quantification of measurement error in DTI : Theoretical predictions and validation. Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings. PART 1. ed. Springer Verlag, 2007. pp. 10-17 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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Quantification of measurement error in DTI: Theoretical predictions and validation

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