NAME

       niftitodicom - vtk-dicom CLI

DESCRIPTION

   usage:
              niftitodicom -o directory file.nii [file.dcm ...]

   options:
       -o directory
              The output directory.

       -s --silent
              Do not print anything while executing.

       -v --verbose
              Verbose error reporting.

       --verbatim
              Copy source metadata nearly verbatim.

       --no-reordering
              Never reorder slices, rows, or columns.

       --axial
              Produce axial slices.

       --coronal
              Produce coronal slices.

       --sagittal
              Produce sagittal slices.

       --series-description
              Textual description of the series.

       --series-number
              The series number to use.

       --modality
              The modality: MR or CT or SC.

       --uid-prefix
              A DICOM uid prefix (optional).

       --version
              Print the version and exit.

       --build-version
              Print source and build version.

       --help Documentation for niftitodicom.

       This program will convert a NIfTI file into a DICOM series.

       It  reads  the NIfTI file header and does the best job that it can to generate a series of
       DICOM files.  To help it along, you can provide a DICOM file from the same series  on  the
       command  line  after the NIfTI file, or even better, list all of the DICOM files that were
       used as the source of the data in the NIfTI file.  Study-related meta data will be  copied
       from these DICOM files into the output DICOM files.

       Unless  the  --no-reordering option is provided, it will ensure that the images are in the
       usual orientation (right is left, posterior is down) by reordering the columns or rows  as
       compared to the NIFTI file.

       If the NIFTI file is floating-point, then the data might be rescaled when written to DICOM
       as 16-bit integers.  If any data values are too large to fit into 16 bits,  then  all  the
       data will be scaled down.  If the data values all have a magnitude smaller than 2.05, then
       all the data will be scaled up by a factor of 1000.

AUTHOR

       This  manual  page was written by Mathieu  Malaterre  <malat@debian.org>  for  the  Debian
       GNU/Linux system, but may be used by others.