Many Linux users are obsessed with achieve leadership at the desk. For them it is not about spreading free software and its 4 freedoms but to defeat Microsoft. The fact that the market for personal computers has peaked, and that Google and Apple's actions on mobile phones are much more dangerous than Microsoft's in their best (worst) days, they don't seem to care.
Nor are they able to enjoy leadership achieved in specific niches such as the cloud, web servers or supercomputers. They prefer to waste time in sterile discussions with fans of Photoshop or Excel.
This is why my New Years resolution is make known free software tools that can be used with great success in sectors in which most of us who write on the subject do not usually notice.
In this post we are going to talk about lin4neuroA distribution that should be considered by those interested in human brain imaging.
Without a doubt, taking into account what governments and private citizens spend on health, any savings in the cost of licenses without loss in the quality of care is a worthy goal to achieve. It is a sector where free and open source software has a lot to give.
Analyzing neuroimaging with Linux. A great starting point for students and professionals
It is a derived version of Ubuntu made by a professor at the Japanese university of Tsukuba. It is based on Ubuntu 16.04 and seems not to be updated since 2017. However, it still constitutes a good starting point for neuroimaging professionals to become familiar with open source applications and students do practical work.
The analyzed images can be shared easily.
In the list of programs I include the links to their respective pages whenever possible.
Please note that I am not a doctor. Although with the help of Google I tried to make the translations as correct as possible, I may have screwed up. I already appreciate any correction.
Among the applications included in the distribution we can mention:
3D slicer: This application It includes algorithms for the analysis of images obtained by functional magnetic resonance imaging and by diffusion tensor. They can also be used for image-guided therapy.
AFNI: SCHEDULE for the processing and analysis of data obtained from magnetic resonance images.
UCL Way Diffusion MRI Toolki: I'm going to put the description in English so as not to screw up. For diffusion MRI processing. I interpret it to be for diffuse magnetic resonance imaging analysis. If there is an imaging specialist in the room who can clarify the issue for us, below is the comment form. Link
caret: This application allows the user to create, view and manipulate reconstructions of surfaces of the brain and cerebral cortex.
Connectome Analyzer: Analysis of the connections between resources from any source (DSI, DTI, QBall, rs-fMRI, etc.) at different scales (global, subnets and local).
Connectome Viewer: connects multimodal and multiscale neuroimaging and network data sets for analysis and visualization in Python.
FSL: Image analysis and statistical tools for fMRI, MRI, and DTI brain imaging data. Link
Ginkgo CADx: This application is a pictures viewer saved under the DICOM standard.
ITK-Snap: Program for the segmentation of structures in 3D medical images. Link
minc toolkit: Application for handling MINC files
MITK: Tools for the development of interactive software for medical image processing.
MITK Diffusion: The program includes a selection of image analysis algorithms for diffusion-weighted magnetic resonance imaging.
MRIConvert: Es a utility medical image file converter that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99 / Analyze, BrainVoyager and MetaImage volume formats.
MRIcron: It is a tool visualization and analysis of images obtained by magnetic resonance (functional).
mrtrix: It is a set of tools to perform white matter tractography on diffusion-weighted magnetic resonance imaging in a robust manner to cross fibers, using restricted spherical deconvolution (CSD) and probabilistic streamlines.
Virtual NMR: Produces a realistic simulation of an MRI scanner.