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. [10.1109/NSSMIC.2014.7430956].

Performances of Principal Component Analysis for the extraction of respiratory signal from Time-of-Flight PET coincidences stream

PRESOTTO, LUCA
Primo
;
DE BERNARDI, ELISABETTA
Secondo
;
Gilardi, M;
2016

Abstract

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.
poster + paper
Nuclear and High Energy Physics; Radiology, Nuclear Medicine and Imaging
English
IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014
2014
2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014
9781479960972
2016
1
4
7430956
none
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. [10.1109/NSSMIC.2014.7430956].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/132926
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