Time alignment of time of flight positron emission tomography using the background activity of LSO

Rothfuss, H.; Moor, Andrew; Young, John W.; Panin, Vladimir; Hayden, Charles

doi:10.1109/nssmic.2013.6829400

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…Concerning timing calibration, various traditional calibration approaches exist, e.g. using dedicated reference detectors (Thompson et al 2005, Bergeron et al 2009, Hancock and Thompson 2010, intrinsic characteristics of the scintillation material (Rothfuss et al 2013), or even clinical data (Werner and Karp 2013). Many approaches are founded on minimizing a matrix equation (Mann et al 2009) for a given norm (e.g.…”

Section: Introductionmentioning

confidence: 99%

Holistic evaluation of a machine learning-based timing calibration for PET detectors under varying data sparsity

Naunheim,

Mueller,

Nadig

et al. 2024

Phys. Med. Biol.

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Objective.Modern PET scanners offer precise TOF information, improving the SNR of the reconstructed images. Timing calibrations are performed to reduce the worsening effects of the system components and provide valuable TOF information. Traditional calibration procedures often provide static or linear corrections, with the drawback that higher-order skews or event-to-event corrections are not addressed. Novel research demonstrated significant improvements in the reachable timing resolutions when combining conventional calibration approaches with machine learning, with the disadvantage of extensive calibration times infeasible for a clinical application. In this work, we made the first steps towards an in-system application and analyzed the effects of varying data sparsity on a machine learning timing calibration, aiming to accelerate the calibration time. Furthermore, we demonstrated the versatility of our calibration concept by applying the procedure for the first time to analog readout technology.Approach. We modified experimentally acquired calibration data used for training regarding their statistical and spatial sparsity, mimicking reduced measurement time and variability of the training data. Trained models were tested on unseen test data, characterized by fine spatial sampling and rich statistics. In total, 80 decision tree models with the same hyperparameter settings, were trained and holistically evaluated regarding data scientific, physics-based, and PET-based quality criteria. Main results.The calibration procedure can be heavily reduced from several days to some minutes without sacrificing quality and still significantly improving the timing resolution from (304 ± 5) ps to (216 ± 1) ps compared to conventionally used analytical calibration methods. Significance. This work serves as the first step in making the developed machine learning-based calibration suitable for an in-system application to profit from the method’s capabilities on the system level. Furthermore, this work demonstrates the functionality of the methodology on detectors using analog readout technology. The proposed holistic evaluation criteria here serve as a guideline for future evaluations of machine learning-based calibration approaches.

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Section: Introductionmentioning

confidence: 99%

Holistic evaluation of a machine learning-based timing calibration for PET detectors under varying data sparsity

Naunheim,

Mueller,

Nadig

et al. 2024

Phys. Med. Biol.

View full text Add to dashboard Cite

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“…Several calibrations on the scanner level have been developed to remove time skews and improve the achievable CTR. While some techniques are based on a known radiation source position (Perkins et al 2005, Li 2019), other calibrations utilize a reference detector (Thompson et al 2005, Bergeron et al 2009, Hancock and Thompson 2010, and even the intrinsic radiation of Lu-based scintillation crystals can be employed to correct time skews (Rothfuss et al 2013). Timing calibration can also be performed without specialized data acquisition by using just clinical data, as demonstrated in (Werner and Karp 2013), and deep learning techniques are also finding their way into calibration (Chen and Liu 2021).…”

Section: Introductionmentioning

confidence: 99%

Analysis of a convex time skew calibration for light sharing-based PET detectors

et al. 2023

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Objective. Positron emission tomography (PET) detectors providing attractive coincidence time resolutions (CTRs) offer time-of-flight information, resulting in an improved signal-to-noise ratio of the PET image. In applications with photosensor arrays that employ timestampers for individual channels, timestamps typically are not time synchronized, introducing time skews due to different signal pathways. The scintillator topology and transportation of the scintillation light might provoke further skews. If not accounted for these effects, the achievable CTR deteriorates. We studied a convex timing calibration based on a matrix equation. In this work, we extended the calibration concept to arbitrary structures targeting different aspects of the time skews and focusing on optimizing the CTR performance for detector characterization. The radiation source distribution, the stability of the estimations, and the energy dependence of calibration data are subject to the analysis. Approach. A coincidence setup, equipped with a semi-monolithic detector comprising 8 LYSO slabs, each 3.9mm×31.9mm×19.0mm, and a one-to-one coupled detector with 8×8 LYSO segments of 3.9mm×3.9mm×19.0mm volume is used. Both scintillators utilize a dSiPM (DPC3200-22-44, Philips Digital Photon Counting) operated in first photon trigger. The calibration was also conducted with solely one-to-one coupled detectors and extrapolated for a slab-only setup. Main results. All analyzed hyperparameters show a strong influence on the calibration. Using multiple radiation positions improved the skew estimation. The statistical significance of the calibration dataset and the utilized energy window was of great importance. Compared to a one-to-one coupled detector pair achieving CTRs of 224 ps the slab detector configuration reached CTRs down to 222 ps, demonstrating that slabs can compete with a clinically used segmented detector design. Significance. This is the first work that systematically studies the influence of hyperparameters on skew estimation and proposes an extension to arbitrary calibration structures (e.g., scintillator volumes) of a known calibration technique.

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A fully automated and scalable timing probe-based method for time alignment of the LabPET II scanners

Samson

Thibaudeau

Bouchard

et al. 2018

Nuclear Instruments and Methods in Physics Research Section A:

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Time alignment of time of flight positron emission tomography using the background activity of LSO

Cited by 5 publications

References 4 publications

Holistic evaluation of a machine learning-based timing calibration for PET detectors under varying data sparsity

Holistic evaluation of a machine learning-based timing calibration for PET detectors under varying data sparsity

Analysis of a convex time skew calibration for light sharing-based PET detectors

A fully automated and scalable timing probe-based method for time alignment of the LabPET II scanners

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