Corpus ID: 231846492

A Practical Model-based Segmentation Approach for Accurate Activation Detection in Single-Subject functional Magnetic Resonance Imaging Studies

  title={A Practical Model-based Segmentation Approach for Accurate Activation Detection in Single-Subject functional Magnetic Resonance Imaging Studies},
  author={Wei-Chen Chen and Ranjan Maitra},
Functional Magnetic Resonance Imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low-signal contexts and single-subject studies. Accurate activation detection can be guided by the fact that very few voxels are, in reality, truly activated and that activated voxels are spatially localized, but it is challenging to incorporate both these facts. We provide a computationally feasible and methodologically sound model-based… Expand

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  • A. Howseman, R. Bowtell
  • Computer Science, Medicine
  • Philosophical transactions of the Royal Society of London. Series B, Biological sciences
  • 1999
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