Modules:DicomToNRRD-3.4

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Module Name

DWI Dicom To NRRD

General Information

Module Type & Category

Type: Command line module

Category: Converter

Authors, Collaborators & Contact

• Author: Xiaodong Tao (with contribution from Vince Magnotta and Hans Johnson)
• Contact: taox @ research.ge.com

Module Description

This module converts diffusion weighted MR images in dicom series into Nrrd format for analysis in Slicer. This program has been tested on only a limited subset of DTI dicom formats available from Siemens, GE, and Phillips scanners. It does not yet support dicom multi-frame data. The program parses dicom header to extract necessary information about measurement frame, diffusion weighting directions, b-values, etc, and write out a nrrd image.

Usage

./DicomToNrrdConverter --help

USAGE:

   d:\Builds\Slicer3\lib\Slicer3\Plugins\Release\DicomToNrrdConverter.exe
                                        [--processinformationaddress
                                        <std::string>] [--xml] [--echo]
                                        [--] [--version] [-h] <std::string>
                                        <std::string>


Where:

   --processinformationaddress <std::string>
     Address of a structure to store process information (progress, abort,
     etc.). (default: 0)

   --xml
     Produce xml description of command line arguments (default: 0)

   --echo
     Echo the command line arguments (default: 0)

   --,  --ignore_rest
     Ignores the rest of the labeled arguments following this flag.

   --version
     Displays version information and exits.

   -h,  --help
     Displays usage information and exits.

   <std::string>
     (required)  Directory holding Dicom series

   <std::string>
     (required)  Nrrd header file name


   Description: Converts diffusion weighted MR images in dicom series into
   Nrrd format.

   Author(s): Xiaodong Tao

   Acknowledgements: This work is part of the National Alliance for Medical
   Image Computing (NAMIC), funded by the National Institutes of Health
   through the NIH Roadmap for Medical Research, Grant U54 EB005149.