Camino (diffusion MRI toolkit)

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Camino [1] is a free open source diffusion MRI image reconstruction toolkit written in Java (programming language). It includes all major diffusion reconstruction techniques such as Diffusion tensor imaging, q-ball and PAS-MRI, as well as white matter tractography algorithms.

The name Camino is derived from the Spanish word Camino meaning route or track. Unfortunately, the same word in Italian means fireplace, which has little to do with diffusion image reconstruction.

Some of Camino's features are:

   * Fitting the Diffusion Tensor to diffusion-weighted MRI data.
   * Fitting 2 and 3-tensor models.
   * Generating synthetic data for testing.
   * Advanced reconstruction algorithms including RESTORE, q-ball, 
     and maximum-entropy spherical deconvolution (including PAS-MRI).
   * Deterministic and probabilistic tractography (PICo), including:
         o Models of uncertainty for one-tensor and two-tensor data.
         o Multiple-ROI processing.
         o Output connection probability maps, or save streamlines
           in raw binary or OOGL (GeomView) format.
   * Full documentation via
         o Unix man pages
         o A variety of case studies illustrating common tasks
         o Standard javadoc for the source code. 

Diffusion MRI is an MR imaging modality which is capable of measuring the bulk diffusive motion of water in biological systems non-invasively. Although primarily used as a research tool, Diffusion MRI is slowly finding a niche in clinical environments. Since the invention of Diffusion Tensor Imaging (DTI), the field has grown rapidly to encompass a large number of applications, particularly in neuroimaging.

In order to address shortcomings of the original DTI technique, several novel reconstruction algorithms have been proposed capable of resolving more complex microstructure from diffusion scan data. Additionally, tractography techniques based on these reconstruction methods have multiplied in number and complexity. Camino is an attempt to unify this important body of work under a single framework and enable researchers to investigate these new techniques.

Camino is developed and maintained by a team of researchers at University College London's Centre for Medical Image Computing[2], lead by Dr. Daniel Alexander. Other Camino developers are Phil Cook, Matt Hall, Kiran Seunarine, Shahrum Nedjati-Gilani, Bai Yu and Phillip Batchelor.