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Integrating structural and functional brain connectivity image, signal, and data processing problems

  • Giuseppe Baselli
  • , Niels Bergsland
  • , Isa Costantini
  • , Ottavia Dipasquale
  • , Elisa Scaccianoce
  • , Marcella Laganà
  • , Laura Pelizzari
  • , Mario Clerici
  • , Francesca Baglio
  • Polytechnic University of Milan
  • IRCCS Fondazione Don Carlo Gnocchi - Milano

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Resting state (RS) functional magnetic resonance images (rsfMRI) were analyzed by spatial independent component analysis (sICA). Functional connectivity (FC) was further analyzed within the identified RS networks either by high dimension sICA or by local clustering. The latter approach permitted to drive a matched structural connectivity (SC) based on probabilistic tractography between the same clusters. Cortex segmentation tools ad diffusion MRI were used to correlate fiber and cortical damage. Methods and results are here compared concerning the translational fall-outs and the applicability in the evaluation and follow-up of neurodegenerative diseases. Emphasis is given to the integration of image, signal, and data processing methods.

Original languageEnglish
Title of host publication2015 AEIT International Annual Conference, AEIT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9788887237283
DOIs
StatePublished - 2015
EventAEIT International Annual Conference: A Sustainable Development in the Mediterranean Area, AEIT 2015 - Naples, Italy
Duration: Oct 14 2015Oct 16 2015

Publication series

Name2015 AEIT International Annual Conference, AEIT 2015

Conference

ConferenceAEIT International Annual Conference: A Sustainable Development in the Mediterranean Area, AEIT 2015
Country/TerritoryItaly
CityNaples
Period10/14/1510/16/15

Keywords

  • Brain tractography
  • Functional brain connectivity
  • Independent component analysis
  • Structural brain connectivity

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