Cancer Imaging Phenomics Toolkit (CaPTk)  1.9.0
Brain Cancer: Population Atlas

This application facilitates the users to generate population atlases for patients with different tumor subgroups [1] to emphasize their heterogeneity.


  1. Segmentation labels of the tumor sub-regions: Non-enhancing tumor core (Label=1), Enhancing tumor core (Label=4)
  2. Standard atlas: A standard atlas to map all the patients in a unified space. Atlas should have region numbers in the ascending order, such as 1,2,3,...,n.
  3. Batch File: A csv file having patients' IDs, group (atlas) number, and path to the actual segmented image. Atlas numbers should be in the ascending order, such as 1,2,3,...,n. Segmentation images should be in the same space as the standard atlas (Note that the CSV file should be in ASCII format, and the CSV file should have the following column headers in any sequence: PATIENT_IDS,IMAGES, ATLAS_LABELS).


  1. Launch the Population Atlases application using the 'Applications -> Population Atlas' menu option.
  2. Specify the Input batch file (e.g., Data_of_multiple_patients) in .csv format, Atlas file with delineated region-of-interests in .nii.gz format, and Output directories.
  3. Click on 'Run PopulationAtlas" and the atlases will be displayed in the visualization window.
    1. The atlases (.nii.gz files) and location features i.e., percentage distribution of the tumors in different sub-regions of the standard atlas template (.csv file) will be saved in the Output directory.
  4. The output atlases can be overlayed on the Jacobs atlas (jakob_stripped_with_cere_lps_256256128.nii.gz) given in the corresponding sample data folder.
  • This application is also available as with a stand-alone CLI for data analysts to build pipelines around, using the following example command:
    ${CaPTk_InstallDir}/bin/PopulationAtlases.exe -i C:/LabelsFile -a C:/AtlasFile -o C:/populationAtlasesOutput


  1. M. Bilello, H. Akbari, X. Da, J.M.Pisapia, S.Mohan, R.L.Wolf, D.M.O'Rourke, M.Martinez-Lage, C.Davatzikos. "Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma", Neuroimage Clin. 12:34-40, 2016, DOI:10.1016/j.nicl.2016.03.007