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.

Computation and management of weighted activation vectors in support to fMRI analysis of clinical subjects

Binaghi, Elisabetta;Vergani, Alberto A.;Pedoia, Valentina;Balbi, Sergio
2019

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.
http://www.tandfonline.com/loi/tciv20
brain tumour studies; clustering; data reduction; fMRI; medical software; statistical parametric map; Computational Mechanics; Biomedical Engineering; Radiology, Nuclear Medicine and Imaging; Computer Science Applications1707 Computer Vision and Pattern Recognition
Binaghi, Elisabetta; Vergani, Alberto A.; Montalbetti, Andrea; Minotto, Renzo; Pedoia, Valentina; Strocchi, Sabina; Balbi, Sergio
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11383/2073507
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