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ABSTRACT
In the present work, we investigate the usefulness of a new representation of the results obtained by fMRI data analysis, named weighted activation vector (WAV), built based on statistical parametric mapping. A software package for the generation and management of WAVs is illustrated. It is designed to support single-subject, multi-temporal and collective brain tumour studies. As seen in our experimental context, the combined use of WAVs and statistical parametric maps (SPMs) improves the quality of medical decisions before and after neurosurgical practice. Clustering techniques applied to WAVs can be efficiently analysed and optimised in an attempt to discover relevant properties of collective data.
Acknowledgements
We thank Dr Andrea Costantino, Dr Samuele Martinelli and Dr Valerio Sommaruga for their precious help in developing technical tools and analyses of experimental data.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
Elisabetta Binaghi
Elisabetta Binaghi received the degree in Physics from the University of Milan, Italy, in 1982. Since March 2002 she has been Associate Professor of Image Processing at the University of Insubria of Varese, Italy and since 2005 head of the Centre of Research in Image Analysis and Medical Informatics. Main interests concern Pattern Recognition and Computational Intelligence. She collaborated to projects in the fields of Medical Informatics and Remote Sensing and Environment, within national and international research programmes.