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Please use this identifier to cite or link to this item: http://hdl.handle.net/10277/511

Authors: Pedoia, Valentina
Internal Tutor: BINAGHI, ELISABETTA
Co-tutor: BALBI, SERGIO
Title: Functional and structural MRI image analysis for brain glial tumors treatment
Abstract: This Ph.D Thesis is the outcome of a close collaboration between the Center for Research in Image Analysis and Medical Informatics (CRAIIM) of the Insubria University and the Operative Unit of Neurosurgery, Neuroradiology and Health Physics of the University Hospital ”Circolo Fondazione Macchi”, Varese. The project aim is to investigate new methodologies by means of whose, develop an integrated framework able to enhance the use of Magnetic Resonance Images, in order to support clinical experts in the treatment of patients with brain Glial tumor. Both the most common uses of MRI technology for non-invasive brain inspection were analyzed. From the Functional point of view, the goal has been to provide tools for an objective reliable and non-presumptive assessment of the brain’s areas locations, to preserve them as much as possible at surgery. From the Structural point of view, methodologies for fully automatic brain segmentation and recognition of the tumoral areas, for evaluating the tumor volume, the spatial distribution and to be able to infer correlation with other clinical data or trace growth trend, have been studied. Each of the proposed methods has been thoroughly assessed both qualitatively and quantitatively. All the Medical Imaging and Pattern Recognition algorithmic solutions studied for this Ph.D. Thesis have been integrated in GliCInE: Glioma Computerized Inspection Environment, which is a MATLAB prototype of an integrated analysis environment that offers, in addition to all the functionality specifically described in this Thesis, a set of tools needed to manage Functional and Structural Magnetic Resonance Volumes and ancillary data related to the acquisition and the patient.
Keywords: MRI analysis, brain segmentatio, glial tumor, functional MRI, statistical parametric map.
Subject MIUR : INF/01 INFORMATICA
Issue Date: 2013
Language: eng
Doctoral course: Informatica
Academic cycle: 25
Publisher: Università degli Studi dell'Insubria
Other information: Cotutela con il Dipartimento di Biotecnologie e Scienze della Vita, Universiità degli Studi dell'Insubria.
Citation: Pedoia, V.Functional and structural MRI image analysis for brain glial tumors treatment (Doctoral Thesis, Università degli Studi dell'Insubria, 2013).

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