MALPEM v1.3 - Whole brain segmentation framework

This is an updated release of MALPEM. If you have any comments or encounter any problems please contact: ledig.christian@gmail.com

Release Notes (v1.3)

malpem-1.3 will produce slightly different results to malpem-1.2.
Compare report of atlas image m100 for malpem-1.2 and malpem-1.3

Functional

• Updated initial N4 bias correction. Instead of potentially using OTSU mask now always use the complete image domain as foreground.
• Always perform two N4 bias correctios (1st: N4 on full image domain, 2nd: N4 w/ mask) regardless of whether user specified a mask
• Updated installer script to allow user to select among various version

Reproducibility

• Fix issue #8 : Fixed ITK threads to 8 to make N4 bias correction deterministic (depends on number of threads)

Robustness/Compatibility

• Fix issue #9 : Ensure input image and mask have numerically same header information to avoid occasional N4 failing. Ensure N4 doesn't fail silently in case of another unexpected problem.
• Fix issue #2 : Added 'export PROOT_NO_SECCOMP=1' to avoid Error 'root info: pid XXX: terminated with signal 11'
• Set ingore_errors=True when attempting to delete temporary files when --cleanup flag is used

Other

• corrected unit from mm^3 to ml in report csv
• removed unused imports, cosmetics

General

The MALPEM distribution package consists of software and data files needed to perform a robust bias correction, brain extraction, and brain segmentation of a magnetic resonance brain image into 138 cortical and subcortical structures.

It was developed by Christian Ledig in the BioMedIA group at Imperial College London, UK.

Acknowledgement: Thanks to all co-authors mentioned below who contributed to the development of the employed methodology. Special thanks to Andreas Schuh for implementing the image registration and giving valuable advice on the distribution of this software package.

If you use any part of this software for your brain image analysis, please cite the following papers:

Framework and segmentation

C. Ledig, R. A. Heckemann, A. Hammers, J. C. Lopez, V. F. J. Newcombe, A. Makropoulos,
J. Loetjoenen, D. Menon and D. Rueckert,
"Robust whole-brain segmentation: Application to traumatic brain injury",
Medical Image Analysis, 21(1), pp. 40-58, 2015.

Brain extraction

R. Heckemann, C. Ledig, K. R. Gray, P. Aljabar, D. Rueckert, J. V. Hajnal, and A. Hammers,
"Brain extraction using label propagation and group agreement: pincram",
PLoS ONE, 10(7), pp. e0129211, 2015.

MALPEM v1.2 - Whole brain segmentation framework

This is the first public release of MALPEM. If you have any comments or encounter any problems please contact: christian.ledig@imperial.ac.uk

The MALPEM distribution package consists of software and data files needed to perform a robust bias correction, brain extraction, and brain segmentation of a magnetic resonance brain image into 138 cortical and subcortical structures.

It was developed by Christian Ledig in the BioMedIA group at Imperial College London, UK.

Acknowledgement: Thanks to all co-authors mentioned below who contributed to the development of the employed methodology. Special thanks to Andreas Schuh for implementing the image registration and giving valuable advice on the distribution of this software package.

If you use any part of this software for your brain image analysis, please cite the following papers:

Framework and segmentation

C. Ledig, R. A. Heckemann, A. Hammers, J. C. Lopez, V. F. J. Newcombe, A. Makropoulos,
J. Loetjoenen, D. Menon and D. Rueckert,
"Robust whole-brain segmentation: Application to traumatic brain injury",
Medical Image Analysis, 21(1), pp. 40-58, 2015.

Brain extraction

R. Heckemann, C. Ledig, K. R. Gray, P. Aljabar, D. Rueckert, J. V. Hajnal, and A. Hammers,
"Brain extraction using label propagation and group agreement: pincram",
PLoS ONE, 10(7), pp. e0129211, 2015.