An iterative two-threshold analysis for single-subject functional MRI of the human brain.

Objectives: Current thresholding strategies for the analysis of functional MRI (fMRI) datasets may suffer from specific limitations (e.g. with respect to the required smoothness) or lead to reduced performance for a low signal-to-noise ratio (SNR). Although a previously proposed two-threshold (TT) m...

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Publicado en:European Radiology Vol. 21; no. 11; pp. 2369 - 2388
Autores principales: Auer T, Schweizer R, Frahm J, Auer, Tibor, Schweizer, Renate, Frahm, Jens
Formato: research Journal Article
Publicado: Springer Nature Nov2011
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2011
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      pub: Springer Nature
      place: New York, New York
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        atl: An iterative two-threshold analysis for single-subject functional MRI of the human brain.
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        au:
          Auer T
          Schweizer R
          Frahm J
          Auer, Tibor
          Schweizer, Renate
          Frahm, Jens
        affil: Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Am Fassberg 11, 37070 Göttingen, Germany
      sug:
        subj:
          Brain Pathology
          Brain Mapping Methods
          Image Processing, Computer Assisted Methods
          Magnetic Resonance Imaging Methods
          Adult
          Algorithms
          Computer Simulation
          Epilepsy, Temporal Lobe Diagnosis
          Epilepsy, Temporal Lobe Pathology
          Male
          Models, Statistical
          ROC Curve
          Walking
          Adult: 19-44 years
          Male
      ab: Objectives: Current thresholding strategies for the analysis of functional MRI (fMRI) datasets may suffer from specific limitations (e.g. with respect to the required smoothness) or lead to reduced performance for a low signal-to-noise ratio (SNR). Although a previously proposed two-threshold (TT) method offers a promising solution to these problems, the use of preset settings limits its performance. This work presents an optimised TT approach that estimates the required parameters in an iterative manner.Methods: The iterative TT (iTT) method is compared with the original TT method, as well as other established voxel-based and cluster-based thresholding approaches and spatial mixture modelling (SMM) for both simulated data and fMRI of a hometown walking task at different experimental settings (spatial resolution, filtering and SNR).Results: In general, the iTT method presents with remarkable sensitivity and good specificity that outperforms all conventional approaches tested except for SMM in a few cases. This also holds true for challenging conditions such as high spatial resolution, the absence of filtering, high noise level, or a low number of task repetitions.Conclusion: Thus, iTT emerges as a good candidate for both scientific fMRI studies at high spatial resolution and more routine applications for clinical purposes.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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