Cancer Imaging Phenomics Toolkit (CaPTk)  1.8.0.Beta
BraTS Pre-processing Pipeline

REQUIREMENTS:

  1. 4 structural MRI images (T1, T1CE, T2, FLAIR)

USAGE:

This CLI-only application takes 4 structural brain MRIs as input and performs the following steps [1-3]:

  1. Re-orientation to LPS/RAI
  2. N4 Bias correction
  3. Co-registration to T1CE
  4. Registration to SRI-24 atlas [4]
  5. Apply registration to re-oriented image to maximize image fidelity
  6. OPTIONAL: Skull-stripping
  7. OPTIONAL: Tumor Segmentation

Example command:

${CaPTk_InstallDir}/bin/BraTSPipeline.exe -t1 C:/test/t1.nii.gz -t1c C:/test/t1ce.nii.gz -t2 C:/test/t2.nii.gz -fl C:/test/flair.nii.gz -o C:/test/outputDir 

NOTE: This applications takes ~30 minutes to finish on an 8-core Intel i7 with 16GB of RAM.


Reference:

  1. B. H. Menze, A. Jakab, S. Bauer, J. Kalpathy-Cramer, K. Farahani, J. Kirby, et al. "The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)", IEEE Transactions on Medical Imaging 34(10), 1993-2024 (2015) DOI:10.1109/TMI.2014.2377694
  2. S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki, J.S. Kirby, et al., "Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features", Nature Scientific Data, 4:170117 (2017) DOI:10.1038/sdata.2017.117
  3. S. Bakas, M. Reyes, A. Jakab, S. Bauer, M. Rempfler, A. Crimi, et al., "Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge", arXiv preprint arXiv:1811.02629 (2018)
  4. T.Rohlfing, N.M.Zahr, E.V.Sullivan, A.Pfefferbaum, "The SRI24 multichannel atlas of normal adult human brain structure", Human Brain Mapping, 31(5):798-819, 2010, DOI:10.1002/hbm.20906