oro.nifti 0.3.1

December 27, 2011

(This article was first published on Rigorous Analytics, and kindly contributed to R-bloggers)

The  package oro.nifti contains functions for the input/output and visualization of medical imaging data that follow either the ANALYZE, NIfTI or AFNI formats.  This package is part of the Rigorous Analytics bundle.

Lightbox display of functional MRI “resting-state” acquisition using image().  The axial plane is used by default.

Lightbox display of functional MRI “resting-state” acquisition using image(, plane=”coronal”).

Llightbox display of functional MRI “resting-state” acquisition using image(, plane=”sagittal”).

Orthographic display of functional MRI “resting-state” acquisition using orthographic().

The latest version of oro.nifti (0.3.1) contains a substantial number of updates:

  • Visualization of NIfTI and ANALYZE S4 objects
    • Aspect ratio is now respected in the overloaded image() function for “nifti” and “anlz” class objects.
    • The plane of acquisition (axial, coronal, sagittal) may now be specified by the user.
    • Min/max values of the data are properly interrogated if cal.min/cal.max or glmin/glmax are not specified.
  • Added accessor/replacement functions for cal.min and cal.max NIfTI metadata fields.
  • Fixed bug in pixdim<- replacement function, should work now.
  • Fixed bug in writeNIfTI so that FSLView can correctly identify the min/max values.
  • Better treatment of Qform and Sform information.

Please use the mailing list at R-Forge or contact [email protected] with any suggestions.

    To leave a comment for the author, please follow the link and comment on their blog: Rigorous Analytics.

    R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

    If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

    Comments are closed.


    Mango solutions

    plotly webpage

    dominolab webpage

    Zero Inflated Models and Generalized Linear Mixed Models with R

    Quantide: statistical consulting and training





    CRC R books series

    Six Sigma Online Training

    Contact us if you wish to help support R-bloggers, and place your banner here.

    Never miss an update!
    Subscribe to R-bloggers to receive
    e-mails with the latest R posts.
    (You will not see this message again.)

    Click here to close (This popup will not appear again)