Multiple testing for neuroimaging via hidden Markov random field

Traditional voxel-level multiple testing procedures in neuroimaging, mostly p-value based, often ignore the spatial correlations among neighboring voxels and thus suffer from substantial loss of power. We extend the local-significance-index based procedure originally developed for the hidden Markov...

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Veröffentlicht in:	Biometrics Jg. 71; H. 3; S. 741 - 750
Hauptverfasser:	Shu, Hai, Nan, Bin, Koeppe, Robert
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Blackwell Publishing Ltd 01.09.2015 International Biometric Society
Schlagworte:	Algorithms Alzheimer disease Alzheimer Disease - diagnostic imaging Alzheimer's disease BIOMETRIC METHODOLOGY biometry Cognitive Dysfunction - diagnostic imaging Computer Simulation False discovery rate Fluorodeoxyglucose F18 Generalized expectation-maximization algorithm Humans image analysis Image Interpretation, Computer-Assisted - methods Imaging, Three-Dimensional - methods Ising model Local significance index Markov analysis Markov chain Markov Chains Medical imaging Models, Statistical Neuroimaging - methods Penalized likelihood Positron-Emission Tomography - methods Radiopharmaceuticals Reproducibility of Results risk Sensitivity and Specificity False discovery rate Ising model Local significance index Alzheimer's disease Penalized likelihood Generalized expectation-maximization algorithm
ISSN:	0006-341X, 1541-0420
Online-Zugang:	Volltext
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