Copyright © German Cancer Research Center (DKFZ), Division of Medical Image Computing (MIC).
The scripts within this repository can be used to convert the LIDC-IDRI data. After calling this script, the image and segmentation data is available in nifti/nrrd format and the nodule characteristics are available in a single comma separated (csv) file.
If you are using these scripts for your publication, please cite as
Michael Goetz, "MIC-DKFZ/LIDC-IDRI-processing: Release 1.0.1", DOI: 10.5281/zenodo.2249217
The scripts uses some standard python libraries (glob, os, subprocess, numpy, and xml), the python library SimpleITK. Additionally, some command line tools from MITK are used. They can be either obtained by building MITK and enabling the classification module or by installing MITK Phenotyping which contains all necessary command line tools.
Following input paths needs to be defined:
The output created of this script consists of Nrrd-Files containing a whole DICOM Series (i.e. an complete 3D CT image), Nifti (.nii.gz) files of the Nodule-Segmentations (3D), Nrrd and Planar Figures (.pf) containing slice-wise segmentations of Nodules.
The data are stored in subfolders, indicating the
There are up to four reader sessions given for each patient and image.
Each combination of Nodule and Expert has an unique 8-digit
The
Based on these definitions, the following files are created:
In addition, the characteristic of the nodules are saved in the file specified in path_to_characteristics and errors occuring during the whole process are recorded in path_to_error_file
The script had been developed using windows. It should be possible to execute it using linux, however this had never been tested. Problems may be caused by the subprocess calls (calling the executables of MITK Phenotyping).
Also, the script had been developed for own research and is not extensivly tested. It is possible that i faulty included some limitations.
I've deloped this script when there were no DICOM Seg-files for the LIDC_IDRI available online. So this script relys on the XML-description, which might not be the best solution. Feel free to extend / write a new solution which makes use of the now available DICOM Seg objects.
If you have suggestions or questions, you can reach the author (Michael Goetz) at m.goetz@dkfz-heidelberg.de
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