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A pattern recognition application framework for biomedical datasets

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Pattern recognition techniques are widely used in the biomedical domain, solving problems ranging from the prediction of cancers to the detection of neural activations in the human brain. Modern biomedical techniques, such as magnetic resonance spectroscopy (MRS) or imaging (MRI), produce voluminous, high-dimensional datasets, whose reliable analysis by medical practitioners requires high-performance, user-friendly programs. Furthermore, researchers who develop such programs need effective algorithm development environments. Scopira facilitates the development of high-performance applications by providing many useful subsystems, flexible and efficient data models, low-level tools such as memory management and serialization, GUI constructs, high-level visualization modules, and the ability to implement parallel algorithms with message-passing interface (MPI). Scopira plug-in extensions have been developed to enable Matlab scripts to easily call any Scopira module, thus facilitating the migration of prototypes to highly efficient C++ applications. Scopira is continuously under development and future capabilities will include the ability to develop distributed programs using agents, applicable to grid-computing data mining applications. Scopira has proven to be a successful programming framework for implementing high-performance biomedical data analysis applications. It is based on C++, an efficient object-oriented language, and the source code is available as an open-source project for other researchers to use and adapt to their own research endeavours. Scopira has been compiled to work on Linux and Windows XP operating systems with a port to the Mac OS under development. Scopira is freely available for download from

Published in:

IEEE Engineering in Medicine and Biology Magazine  (Volume:26 ,  Issue: 2 )