Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/653089D5-88DB-41D8-B939-07EF11D9BF2F | - |
| Αναγνωριστικό | https://doi.org/10.1109/TIP.2022.3159125 | - |
| Αναγνωριστικό | https://ieeexplore.ieee.org/document/9778969 | - |
| Γλώσσα | en | - |
| Μέγεθος | 12 pages | en |
| Τίτλος | Multisubject task-related fMRI data processing via a two-stage generalized canonical correlation analysis | en |
| Δημιουργός | Karakasis Paris | en |
| Δημιουργός | Καρακασης Παρις | el |
| Δημιουργός | Liavas Athanasios | en |
| Δημιουργός | Λιαβας Αθανασιος | el |
| Δημιουργός | Sidiropoulos Nikos | en |
| Δημιουργός | Σιδηροπουλος Νικος | el |
| Δημιουργός | Simos Panagiotis G. | en |
| Δημιουργός | Papadaki Efrosini | en |
| Εκδότης | Institute of Electrical and Electronics Engineers | en |
| Περίληψη | Functional magnetic resonance imaging (fMRI) is one of the most popular methods for studying the human brain. Task-related fMRI data processing aims to determine which brain areas are activated when a specific task is performed and is usually based on the Blood Oxygen Level Dependent (BOLD) signal. The background BOLD signal also reflects systematic fluctuations in regional brain activity which are attributed to the existence of resting-state brain networks. We propose a new fMRI data generating model which takes into consideration the existence of common task-related and resting-state components. We first estimate the common task-related temporal component, via two successive stages of generalized canonical correlation analysis and, then, we estimate the common task-related spatial component, leading to a task-related activation map. The experimental tests of our method with synthetic data reveal that we are able to obtain very accurate temporal and spatial estimates even at very low Signal to Noise Ratio (SNR), which is usually the case in fMRI data processing. The tests with real-world fMRI data show significant advantages over standard procedures based on General Linear Models (GLMs). | en |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2023-12-01 | - |
| Ημερομηνία Δημοσίευσης | 2022 | - |
| Θεματική Κατηγορία | fMRI | en |
| Θεματική Κατηγορία | Generalized CCA | en |
| Θεματική Κατηγορία | MAX-VAR | en |
| Βιβλιογραφική Αναφορά | P. A. Karakasis, A. P. Liavas, N. D. Sidiropoulos, P. G. Simos and E. Papadaki, "Multisubject task-related fMRI data processing via a two-stage generalized canonical correlation analysis," IEEE Trans. Image Process., vol. 31, pp. 4011-4022, doi: 10.1109/TIP.2022.3159125. | en |
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