Improving Depth, Energy and Timing Estimation in PET Detectors with Deconvolution and Maximum Likelihood Pulse Shape Discrimination

Eric Berg, Emilie Roncali, Will Hutchcroft, Jinyi Qi, Simon R Cherry

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

In a scintillation detector, the light generated in the scintillator by a gamma interaction is converted to photoelectrons by a photodetector and produces a time-dependent waveform, the shape of which depends on the scintillator properties and the photodetector response. Several depth-of-interaction (DOI) encoding strategies have been developed that manipulate the scintillator's temporal response along the crystal length and therefore require pulse shape discrimination techniques to differentiate waveform shapes. In this work, we demonstrate how maximum likelihood (ML) estimation methods can be applied to pulse shape discrimination to better estimate deposited energy, DOI and interaction time (for time-of-flight (TOF) PET) of a gamma ray in a scintillation detector. We developed likelihood models based on either the estimated detection times of individual photoelectrons or the number of photoelectrons in discrete time bins, and applied to two phosphor-coated crystals (LFS and LYSO) used in a previously developed TOF-DOI detector concept. Compared with conventional analytical methods, ML pulse shape discrimination improved DOI encoding by 27% for both crystals. Using the ML DOI estimate, we were able to counter depth-dependent changes in light collection inherent to long scintillator crystals and recover the energy resolution measured with fixed depth irradiation (11.5% for both crystals). Lastly, we demonstrated how the Richardson-Lucy algorithm, an iterative, ML-based deconvolution technique, can be applied to the digitized waveforms to deconvolve the photodetector's single photoelectron response and produce waveforms with a faster rising edge. After deconvolution and applying DOI and time-walk corrections, we demonstrated a 13% improvement in coincidence timing resolution (from 290 to 254 ps) with the LFS crystal and an 8% improvement (323 to 297 ps) with the LYSO crystal.

Original languageEnglish (US)
Article number7486045
Pages (from-to)2436-2446
Number of pages11
JournalIEEE Transactions on Medical Imaging
Volume35
Issue number11
DOIs
StatePublished - Nov 1 2016

Fingerprint

Deconvolution
Maximum likelihood
Phosphors
Detectors
Crystals
Photoelectrons
Photodetectors
Scintillation counters
Light
Gamma Rays
Maximum likelihood estimation
Bins
Gamma rays
Irradiation

Keywords

  • Depth-of-interaction (DOI)
  • gamma ray detectors
  • maximum likelihood estimation
  • positron emission tomography (PET)
  • pulse shape discrimination

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Improving Depth, Energy and Timing Estimation in PET Detectors with Deconvolution and Maximum Likelihood Pulse Shape Discrimination. / Berg, Eric; Roncali, Emilie; Hutchcroft, Will; Qi, Jinyi; Cherry, Simon R.

In: IEEE Transactions on Medical Imaging, Vol. 35, No. 11, 7486045, 01.11.2016, p. 2436-2446.

Research output: Contribution to journalArticle

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