Imanova launches MIAKAT™ - software package for the quantitative analysis of PET neuroimaging data

MIAKAT ImanovaLondon, January 04 2016: MIAKAT™ is a fully quantitative suite of analysis tools for PET neuroimaging data. Designed and developed by Prof. Roger Gunn and Dr Graham Searle, MIAKAT™ is downloadable from a dedicated website and is free-to-use for academic applications. MIAKAT™ brings together state of the art tools for the quantitative analysis of PET molecular imaging data in a single user friendly software environment making it straightforward for novice or advanced imaging scientists to efficiently and accurately analyse their data. The software includes functionality for motion correction of dynamic image sequences, neuoranatomical parcellation of regions of interest (ROIs), blood/plasma input function modelling and tracer kinetic modelling for regional or parametric image analyses.

MIAKAT™ is implemented in MATLAB™, and has a central graphical user interface that facilitates “point and click” operation, so that users can concentrate on their data without needing to learn how to use MATLAB™ or other tools. Users can run preconfigured standard analysis workflows, or bespoke pipelines and processes to suit their needs – each analysis is reproducible because of the inbuilt audit trails which ensure consistency and quality.

Prof Roger Gunn, CSO at Imanova says “MIAKAT™ has already enabled state of the art molecular imaging analysis to be applied in a reproducible and high quality manner to data acquired at Imanova for the pharmaceutical industry and academia.  It is exciting to share this tool with the broader academic community so that they can also benefit from these developments.  The software environment makes it easy to incorporate cutting-edge algorithms and the user interface allows for clinical fellows to analyse their data as easily as researchers from the mathematical sciences. More experienced users are encouraged to implement novel techniques within the MIAKAT™ framework and thus contribute to future versions."

For more information, please visit www.miakat.org.

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