Literature DB >> 9430342

Methods for assessing accuracy and reliability in functional MRI.

T H Le1, X Hu.   

Abstract

In this paper, methods for assessing the accuracy and the reliability of functional magnetic resonance imaging techniques are presented. First, a modified receiver operating characteristic analysis is described for evaluating the accuracy of fMRI studies. With this modified approach, the true positives or the activated pixels are estimated based on highly averaged experimental data acquired with the same stimulation/task. Unlike ROC analysis based on simulated activation data, the present approach can be applied to experimentally acquired data without simplifying the activation related changes. To assess the reliability of fMRI studies, the kappa statistic was adopted for evaluating the overall agreement of functional activation maps from repeated experiments in individual subjects. To demonstrate the utility of these techniques, both the ROC analysis and the reliability assessment were applied to quantitatively evaluate the improvement in accuracy and reliability of a retrospective technique for physiological noise reduction in fMRI.

Mesh:

Year:  1997        PMID: 9430342     DOI: 10.1002/(sici)1099-1492(199706/08)10:4/5<160::aid-nbm458>3.0.co;2-a

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  17 in total

1.  Reproducibility of BOLD-based functional MRI obtained at 4 T.

Authors:  C Tegeler; S C Strother; J R Anderson; S G Kim
Journal:  Hum Brain Mapp       Date:  1999       Impact factor: 5.038

2.  Model assessment and model building in fMRI.

Authors:  Mehrdad Razavi; Thomas J Grabowski; Walter P Vispoel; Patrick Monahan; Sonya Mehta; Brent Eaton; Lizann Bolinger
Journal:  Hum Brain Mapp       Date:  2003-12       Impact factor: 5.038

3.  Reproducibility of functional MR imaging results using two different MR systems.

Authors:  Erik-Jan Vlieger; Cristina Lavini; Charles B Majoie; Gerard J den Heeten
Journal:  AJNR Am J Neuroradiol       Date:  2003-04       Impact factor: 3.825

4.  A mutual information-based metric for evaluation of fMRI data-processing approaches.

Authors:  Babak Afshin-Pour; Hamid Soltanian-Zadeh; Gholam-Ali Hossein-Zadeh; Cheryl L Grady; Stephen C Strother
Journal:  Hum Brain Mapp       Date:  2011-05       Impact factor: 5.038

5.  Test-retest reliability in fMRI of language: group and task effects.

Authors:  E Elinor Chen; Steven L Small
Journal:  Brain Lang       Date:  2006-06-05       Impact factor: 2.381

6.  Reproducibility of functional MR imaging: preliminary results of prospective multi-institutional study performed by Biomedical Informatics Research Network.

Authors:  Kelly H Zou; Douglas N Greve; Meng Wang; Steven D Pieper; Simon K Warfield; Nathan S White; Sanjay Manandhar; Gregory G Brown; Mark G Vangel; Ron Kikinis; William M Wells
Journal:  Radiology       Date:  2005-12       Impact factor: 11.105

7.  Automated quality assurance routines for fMRI data applied to a multicenter study.

Authors:  Tony Stöcker; Frank Schneider; Martina Klein; Ute Habel; Thilo Kellermann; Karl Zilles; N Jon Shah
Journal:  Hum Brain Mapp       Date:  2005-06       Impact factor: 5.038

8.  Comparison of fMRI statistical software packages and strategies for analysis of images containing random and stimulus-correlated motion.

Authors:  Victoria L Morgan; Benoit M Dawant; Yong Li; David R Pickens
Journal:  Comput Med Imaging Graph       Date:  2007-06-15       Impact factor: 4.790

9.  Test-retest and between-site reliability in a multicenter fMRI study.

Authors:  Lee Friedman; Hal Stern; Gregory G Brown; Daniel H Mathalon; Jessica Turner; Gary H Glover; Randy L Gollub; John Lauriello; Kelvin O Lim; Tyrone Cannon; Douglas N Greve; Henry Jeremy Bockholt; Aysenil Belger; Bryon Mueller; Michael J Doty; Jianchun He; William Wells; Padhraic Smyth; Steve Pieper; Seyoung Kim; Marek Kubicki; Mark Vangel; Steven G Potkin
Journal:  Hum Brain Mapp       Date:  2008-08       Impact factor: 5.038

10.  A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

Authors:  Jing Zhang; Lichen Liang; Jon R Anderson; Lael Gatewood; David A Rottenberg; Stephen C Strother
Journal:  Neuroinformatics       Date:  2008-05-28
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