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Computes maximum response from Cardiac Magnetic Resonance Images using spatial and voxel wise spline based Bayesian model. This is an implementation of the methods described in Schmid (2011) <doi:10.1109/TMI.2011.2109733> "Voxel-Based Adaptive Spatio-Temporal Modelling of Perfusion Cardiovascular MRI". IEEE TMI 30(7) p. 1305 - 1313.
Version: | 1.1 |
Depends: | R (≥ 3.5.0) |
Imports: | Matrix, splines, fields, graphics, parallel, plotrix |
Suggests: | knitr, rmarkdown, codetools, testthat (≥ 3.0.0), R.rsp |
Published: | 2023-07-19 |
DOI: | 10.32614/CRAN.package.cmR |
Author: | Volker Schmid [aut, cre] |
Maintainer: | Volker Schmid <volker.schmid at lmu.de> |
BugReports: | https://github.com/bioimaginggroup/cmR/issues |
License: | GPL-3 |
URL: | https://bioimaginggroup.github.io/cmr/ |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | cmR results |
Reference manual: | cmR.pdf |
Vignettes: |
CMR usage on example data set |
Package source: | cmR_1.1.tar.gz |
Windows binaries: | r-devel: cmR_1.1.zip, r-release: cmR_1.1.zip, r-oldrel: cmR_1.1.zip |
macOS binaries: | r-release (arm64): cmR_1.1.tgz, r-oldrel (arm64): cmR_1.1.tgz, r-release (x86_64): cmR_1.1.tgz, r-oldrel (x86_64): cmR_1.1.tgz |
Old sources: | cmR archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.