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Data Driven Respiratory Signal Detection in PET Taking Advantage of Time-of-Flight Data

Bertolli, O; Arridge, S; Stearns, CW; Wollenweher, SD; Hutton, BF; Thielemans, K; (2017) Data Driven Respiratory Signal Detection in PET Taking Advantage of Time-of-Flight Data. In: Proceedings of the 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD). IEEE: Strasbourg, France. Green open access

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Abstract

Respiratory gating is a powerful tool for tackling motion-related issues in chest PET imaging. On current scanners the respiratory signal is obtained from external devices, whereas with Data-Driven methods it can be extracted directly from the data. The aim of this work is to show the increased potential of the application of Principal Component Analysis (PCA) on TOF data. We propose a methodology that retains the TOF information and compare it to the non-TOF method. We tested the method on 16 FDG oncology patients, monitored with an RPM camera. To further investigate the benefit of TOF, PCA was selectively applied to sets of TOF bins equidistant from the center. The correlation with the RPM, the level of noise and the respiratory-likeness were analysed for all the obtained respiratory signals. The results of our analysis showed that retaining the TOF information into the sinograms considerably increased the quality of the extracted respiratory signals.

Type: Proceedings paper
Title: Data Driven Respiratory Signal Detection in PET Taking Advantage of Time-of-Flight Data
Event: IEEE Nuclear Science Symposium / Medical Imaging Conference / Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD)
Location: Strasbourg, FRANCE
Dates: 29 October 2016 - 06 November 2016
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/NSSMIC.2016.8069426
Publisher version: https://doi.org/10.1109/NSSMIC.2016.8069426
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Principal component analysis, Correlation, Data mining, Biomedical imaging, Physics, Signal resolution
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Metabolism and Experi Therapeutics
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10060445
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