The current and previous members of the BIC [1] have written and released a large number of image analysis software packages, some of these releases date back to the late 1980′s. The most recognised of these is the MINC file format, toolbox and associated tools.

The MINC file format and toolbox was originally conceived, written and released by Peter Neelin in 1992 due to the frustrations of dealing with multiple file formats from varying scanners and research groups. In the ensuing years many associated tools (image registration, normalisation, visualisation, etc.) were written and have also been released.

The original MINC file format and tools were based upon the NetCDF data format but problems were being encountered with multi-gigabyte datasets, as such a large rewrite of the library was undertaken in 2002–3 in which the data format was changed to HDF in order to support large files and other new features. This release series is called MINC2. Development work on MINC1 was halted at version 1.5.1 in 2006. All the current MINC2 tools are backward compatible with MINC1 format, with exception of the RMINC library and pyminc (based on the MINC2 API), which cannot read MINC1 format files directly.

The current MINC2 library and tools are maintained by a group of developers in various image research labs around the world.

Advanced image processing toolsEdit

These include various image processing applications. Below is a small list of the most important of these programs and their applications.

Geometric distortion correction

Tools to estimate and correct for geometrical distortions caused by imaging gradient non-linearities.


The N3 package, a part of MINC tools, implements a non-parametric method for correction of intensity non-uniformity in MRI data. Its use tends to be an essential first step in any processing sequence.

Registration tools/ANIMAL

This family of algorithms linearly and nonlinearly register two images to each other. The most used, mritotal registers an MRI to standard Talairach space. They are all part of the MNI AutoReg package. ANIMAL is also part of MNI Autoreg and was designed to label the major anatomical regions (the different lobes, corpus callosum, etc.) of a MRI.


INSECT is the algorithm to separate a structural MRI into its three tissue types: white matter, gray matter, and CSF. It is available as part of the classify packages.


SEAL stands for “Sulcal Extraction and Labelling” - which pretty much explains its use as well.

Pipelining toolEdit

Also known as PMP, it is designed to perform a series of processing steps on a large database of images.

Statistical analysis toolsEdit


glim_image is designed for performing VBM (Voxel Based Morphometry) - in other words, it is useful for examining the changes in segmented tissue matter (white matter, gray matter, CSF) as it relates to a linear model.


EMMA (Extensible MATLAB Medical image Analysis) is a toolkit designed to ease the use of MATLAB in the analysis of medical imaging data. It provides functions for reading and writing MINC files, viewing images, performing ROI operations, and performing several popular analyses. Also, there are toolkits for performing kinetic analysis of dynamic PET rCBF (regional cerebral blood flow) and FDG data.


MINC2 library to read and write MINC volumes in R. It also performs linear model analysis.

fMRI statistical analysis

And lastly fMRI statistical analysis is also done using matlab.

Visualization toolsEdit




MNI ray_trace



The MINC package itself and most of the associated tools are licensed under a modified BSD license. The MINC license is shown below but be aware that some packages are released under differing licences such as the GPL. Check the COPYING file in the chosen package for details.

  Copyright 1993-2000, 
  McConnell Brain Imaging Centre
  Montreal Neurological Institute
  McGill University.
  Permission to use, copy, modify, and distribute this software and its
  documentation for any purpose and without fee is hereby granted,
  provided that the above copyright notice appear in all copies.  The
  author and McGill University make no representations about the
  suitability of this software for any purpose.  It is provided "as is"
  without express or implied warranty.

Where to get more infoEdit

There is a MINC-users [2] and MINC-developers [3] mailing list and associated archives. You are welcome to join these mailing lists and post questions.