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 proceedingConference 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 languageEnglish (US)
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings
    Pages10-17
    Number of pages8
    Volume4791 LNCS
    EditionPART 1
    StatePublished - 2007
    Event10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007 - Brisbane, Australia
    Duration: Oct 29 2007Nov 2 2007

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 1
    Volume4791 LNCS
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007
    CountryAustralia
    CityBrisbane
    Period10/29/0711/2/07

    Fingerprint

    Diffusion tensor imaging
    Diffusion Tensor Imaging
    Measurement errors
    Measurement Error
    Quantification
    Noise
    Tensor
    Systematic Error
    Systematic errors
    Imaging
    Imaging techniques
    Tensors
    Prediction
    Random errors
    Random Error
    Magnetic Resonance Imaging
    Magnetic resonance
    Statistical Analysis
    Statistical methods
    Quantify

    ASJC Scopus subject areas

    • Computer Science(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Theoretical Computer Science

    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., Vol. 4791 LNCS, 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).

    Quantification of measurement error in DTI : Theoretical predictions and validation. / Goodlett, Casey; Fletcher, P. Thomas; Lin, Weili; Gerig, Guido.

    Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings. Vol. 4791 LNCS PART 1. ed. 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 proceedingConference 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, vol. 4791 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4791 LNCS, pp. 10-17, 10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007, Brisbane, Australia, 10/29/07.
    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. Vol. 4791 LNCS. 2007. p. 10-17. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
    Goodlett, Casey ; Fletcher, P. Thomas ; Lin, Weili ; Gerig, Guido. / Quantification of measurement error in DTI : Theoretical predictions and validation. Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings. Vol. 4791 LNCS PART 1. ed. 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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