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.