Package: WhiteStripe 2.5.0
WhiteStripe: White Matter Normalization for Magnetic Resonance Images
Shinohara (2014) <doi:10.1016/j.nicl.2014.08.008> introduced 'WhiteStripe', an intensity-based normalization of T1 and T2 images, where normal appearing white matter performs well, but requires segmentation. This method performs white matter mean and standard deviation estimates on data that has been rigidly-registered to the 'MNI' template and uses histogram-based methods.
Authors:
WhiteStripe_2.5.0.tar.gz
WhiteStripe_2.5.0.zip(r-4.7)WhiteStripe_2.5.0.zip(r-4.6)WhiteStripe_2.5.0.zip(r-4.5)
WhiteStripe_2.5.0.tgz(r-4.6-any)WhiteStripe_2.5.0.tgz(r-4.5-any)
WhiteStripe_2.5.0.tar.gz(r-4.7-any)WhiteStripe_2.5.0.tar.gz(r-4.6-any)
WhiteStripe_2.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
WhiteStripe/json (API)
NEWS
| # Install 'WhiteStripe' in R: |
| install.packages('WhiteStripe', repos = c('https://muschellij2.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/muschellij2/whitestripe/issues
- s.hist - Smoothed histogram of image
- t1.voi.hist - Histogram of VOI of T1 template image
- t2.voi.hist - Histogram of VOI of T2 template image
- xvals - Midpoints from VOI histogram
Last updated from:50f1f3fb60. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 147 | ||
| source / vignettes | OK | 180 | ||
| linux-release-x86_64 | OK | 135 | ||
| macos-release-arm64 | OK | 104 | ||
| macos-oldrel-arm64 | OK | 111 | ||
| windows-devel | OK | 130 | ||
| windows-release | OK | 118 | ||
| windows-oldrel | OK | 125 | ||
| wasm-release | OK | 100 |
Exports:download_img_dataget.deriv.smooth.histget.first.modeget.largest.modeget.last.modemake_img_voismooth_histwhitestripewhitestripe_hybridwhitestripe_ind_to_maskwhitestripe_normws_img_data
Dependencies:abindbitopslatticeMatrixmatrixStatsmgcvneurobasenlmeoro.niftiR.methodsS3R.ooR.utilsRcppRNifti
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Download T1 and T2 data | download_img_data |
| Gets nth derivative of smoothed histogram | get.deriv.smooth.hist |
| Get First Peak | get.first.mode |
| Grab largest peak | get.largest.mode |
| Get Last Peak | get.last.mode |
| Make Image VOI | make_img_voi |
| Smoothed histogram of image | s.hist |
| Histogram smoothing for whitestripe | smooth_hist |
| Histogram of VOI of T1 template image | t1.voi.hist |
| Histogram of VOI of T2 template image | t2.voi.hist |
| Performs White Stripe of T1 or T2 Images | whitestripe |
| Hybrid WhiteStripe | hybrid whitestripe_hybrid |
| WhiteStripe Indices to Mask | whitemask whitestripe_ind_to_mask |
| Normalize Image using white stripe | whitestripe_norm |
| Return Filenames of T1 and T2 data | ws_img_data |
| Midpoints from VOI histogram | xvals |
