期刊
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES
卷 2, 期 3, 页码 235-243出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRPMS.2017.2771490
关键词
Dose reduction; image reconstruction; positron emission tomography (PET)-MR; PET
资金
- King's College London
- Imperial College London EPSRC Centre for Doctoral Training in Medical Imaging [EP/L015226/1]
- Wellcome EPSRC Centre for Medical Engineering at King's College London [WT 203148/Z/16/Z]
- EPSRC [EP/M020142/1]
- National Institute for Health Research (NIHR) Biomedical Research Centre Award
- NIHR Healthcare Technology Co-operative for Cardiovascular Disease at Guy's and St Thomas' NHS Foundation Trust
- EPSRC [EP/M020142/1] Funding Source: UKRI
- MRC [MR/N013042/1] Funding Source: UKRI
Positron emission tomography (PET) image reconstruction is highly susceptible to the impact of Poisson noise, and if shorter acquisition times or reduced injected doses are used, the noisy PET data become even more limiting. The recent development of kernel expectation maximization is a simple way to reduce noise in PET images, and we show in this paper that impressive dose reduction can be achieved when the kernel method is used with MR-derived kernels. The kernel method is shown to surpass maximum likelihood expectation maximization (MLEM) for the reconstruction of low-count datasets (corresponding to those obtained at reduced injected doses) producing visibly clearer reconstructions for unsmoothed and smoothed images, at all count levels. The kernel EM reconstruction of 10% of the data had comparable whole brain voxel-level error measures to the MLEM reconstruction of 100% of the data (for simulated data, at 100 iterations). For regional metrics, the kernel method at reduced dose levels attained a reduced coefficient of variation and more accurate mean values compared to MLEM. However, the advances provided by the kernel method are at the expense of possible over-smoothing of features unique to the PET data. Further assessment on clinical data is required to determine the level of dose reduction that can be routinely achieved using the kernel method, whilst maintaining the diagnostic utility of the scan.
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