Abstract
In neuroimaging studies, the type 1 error attributable to the number of independent regional comparisons should be considered. Implemented algorithms approximate the type 1 errors assuming Gaussian or Gaussian-based distribution, are typically for a contiguous/convex volume, and are for conventional hypothesis related to at least one or more clusters of certain size/height. As a complement, a Monte-Carlo algorithm is proposed to calculate the type 1 error of various types of hypotheses a researcher might have, and is applicable to Gaussian and non-Gaussian distributions over non-contiguous, non-convex and convoluted search volume.
Original language | English (US) |
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Pages (from-to) | 11-15 |
Number of pages | 5 |
Journal | IFAC Proceedings Volumes (IFAC-PapersOnline) |
Volume | 36 |
Issue number | 15 |
DOIs | |
State | Published - 2003 |
Event | 5th IFAC Symposium on Modelling and Control in Biomedical Systems 2003 - Melbourne, Australia Duration: Aug 21 2003 → Aug 23 2003 |
Keywords
- Image analysis
- Image processing
- Magnetic resonance imaging
- Monte-carlo simulation
- Positron emission tomography
- Statistical inference
ASJC Scopus subject areas
- Control and Systems Engineering