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

Articolo
Data di Pubblicazione:
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.
Tipologia CRIS:
Articolo su Rivista
Keywords:
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
Elenco autori:
Binaghi, Elisabetta; Vergani, Alberto A.; Montalbetti, Andrea; Minotto, Renzo; Pedoia, Valentina; Strocchi, Sabina; Balbi, Sergio
Autori di Ateneo:
BALBI SERGIO
Link alla scheda completa:
https://irinsubria.uninsubria.it/handle/11383/2073507
Pubblicato in:
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING: IMAGING & VISUALIZATION
Journal
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URL

http://www.tandfonline.com/loi/tciv20
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