PET Reconstruction with an Anatomical MRI Prior Using Parallel Level Sets

Matthias J. Ehrhardt, Pawel Markiewicz, Maria Liljeroth, Anna Barnes, Ville Kolehmainen, John S. Duncan, Luis Pizarro, David Atkinson, Brian F. Hutton, Sebastien Ourselin, Kris Thielemans, Simon R. Arridge

Research output: Contribution to journalArticlepeer-review

43 Citations (Scopus)

Abstract

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) offers unique possibilities. In this paper we aim to exploit the high spatial resolution of MRI to enhance the reconstruction of simultaneously acquired PET data. We propose a new prior to incorporate structural side information into a maximum a posteriori reconstruction. The new prior combines the strengths of previously proposed priors for the same problem: it is very efficient in guiding the reconstruction at edges available from the side information and it reduces locally to edge-preserving total variation in the degenerate case when no structural information is available. In addition, this prior is segmentation-free, convex and no a priori assumptions are made on the correlation of edge directions of the PET and MRI images. We present results for a simulated brain phantom and for real data acquired by the Siemens Biograph mMR for a hardware phantom and a clinical scan. The results from simulations show that the new prior has a better trade-off between enhancing common anatomical boundaries and preserving unique features than several other priors. Moreover, it has a better mean absolute bias-to-mean standard deviation trade-off and yields reconstructions with superior relative l2-error and structural similarity index. These findings are underpinned by the real data results from a hardware phantom and a clinical patient confirming that the new prior is capable of promoting well-defined anatomical boundaries.

Original languageEnglish
Article number7452643
Pages (from-to)2189-2199
Number of pages11
JournalIEEE Transactions on Medical Imaging
Volume35
Issue number9
DOIs
Publication statusPublished - 1 Sep 2016

Keywords

  • Anatomical prior
  • magnetic resonance imaging
  • parallel level sets
  • positron emission tomography
  • Total variation

ASJC Scopus subject areas

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

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