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 language | English |
|---|---|
| Title of host publication | 2015 AEIT International Annual Conference, AEIT 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Print) | 9788887237283 |
| DOIs | |
| Publication status | Published - Feb 19 2016 |
| Event | AEIT International Annual Conference: A Sustainable Development in the Mediterranean Area, AEIT 2015 - Naples, Italy Duration: Oct 14 2015 → Oct 16 2015 |
Other
| Other | AEIT International Annual Conference: A Sustainable Development in the Mediterranean Area, AEIT 2015 |
|---|---|
| Country | Italy |
| City | Naples |
| Period | 10/14/15 → 10/16/15 |
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Keywords
- Brain tractography
- Functional brain connectivity
- Independent component analysis
- Structural brain connectivity
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Biomedical Engineering
Cite this
Integrating structural and functional brain connectivity image, signal, and data processing problems. / Baselli, Giuseppe; Bergsland, Niels; Costantini, Isa; Dipasquale, Ottavia; Scaccianoce, Elisa; Laganà, Marcella; Pelizzari, Laura; Clerici, Mario; Baglio, Francesca.
2015 AEIT International Annual Conference, AEIT 2015. Institute of Electrical and Electronics Engineers Inc., 2016. 7415273.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Integrating structural and functional brain connectivity image, signal, and data processing problems
AU - Baselli, Giuseppe
AU - Bergsland, Niels
AU - Costantini, Isa
AU - Dipasquale, Ottavia
AU - Scaccianoce, Elisa
AU - Laganà, Marcella
AU - Pelizzari, Laura
AU - Clerici, Mario
AU - Baglio, Francesca
PY - 2016/2/19
Y1 - 2016/2/19
N2 - 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.
AB - 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.
KW - Brain tractography
KW - Functional brain connectivity
KW - Independent component analysis
KW - Structural brain connectivity
UR - http://www.scopus.com/inward/record.url?scp=84964869926&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84964869926&partnerID=8YFLogxK
U2 - 10.1109/AEIT.2015.7415273
DO - 10.1109/AEIT.2015.7415273
M3 - Conference contribution
AN - SCOPUS:84964869926
SN - 9788887237283
BT - 2015 AEIT International Annual Conference, AEIT 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -