Recently Principal Component Analysis (PCA) was suggested as a potential way to extract motion signals (e.g: cardiac beat and respiratory signals) from the coincidences stream of the PET scan. Proofs of principle ensued.
PRESOTTO, L., DE BERNARDI, E., Gilardi, M., Gianolli, L., & Bettinardi, V. (2016). Performances of Principal Component Analysis for the extraction of respiratory signal from Time-of-Flight PET coincidences stream. In 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014 (pp.1-4). Institute of Electrical and Electronics Engineers Inc..
Citazione: | PRESOTTO, L., DE BERNARDI, E., Gilardi, M., Gianolli, L., & Bettinardi, V. (2016). Performances of Principal Component Analysis for the extraction of respiratory signal from Time-of-Flight PET coincidences stream. In 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014 (pp.1-4). Institute of Electrical and Electronics Engineers Inc.. |
Tipo: | poster + paper |
Carattere della pubblicazione: | Scientifica |
Presenza di un coautore afferente ad Istituzioni straniere: | No |
Titolo: | Performances of Principal Component Analysis for the extraction of respiratory signal from Time-of-Flight PET coincidences stream |
Autori: | PRESOTTO, L; DE BERNARDI, E; Gilardi, M; Gianolli, L; Bettinardi, V |
Autori: | PRESOTTO, LUCA (Primo) DE BERNARDI, ELISABETTA (Secondo) |
Data di pubblicazione: | 2016 |
Lingua: | English |
Nome del convegno: | IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014 |
ISBN: | 9781479960972 |
Appare nelle tipologie: | 02 - Intervento a convegno |
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