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  • Meeting abstract
  • Open Access

PET/MR: improvement of the UTE μ-maps using modified MLAA

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EJNMMI Physics20152 (Suppl 1) :A58

  • Published:


  • Positron Emission Tomography
  • Technical Physic
  • Hybrid System
  • Attenuation Correction
  • Transmission Scan

For a quantitative analysis in positron emission tomography (PET) or single-photon emission computed tomography (SPECT), attenuation correction (AC) is mandatory. CTscans or transmission scans are common tools for determination of the attenuation μ-map, but in the case of a PET/MR hybrid system it is difficult to associate one of these scans. Many techniques have been developed in order to improve AC for PET/MR. Some methods are based on template- or atlas techniques, other methods apply a segmentation technique based on Dixon or UTE (Ultrashort Echo Time) MR to create the μ-map, followed by a standard OSEM reconstruction (OSEM/DIXON and OSEM/UTE). A different approach for AC has been developed by employing the emission sinogram data in the μ-map derivation. In this context, we modified the iterative MLAA (Maximum-Likelihood reconstruction of Attenuation and Activity) algorithm to improve the resulting emission image from the PET/MR system. We constrained the attenuation map update using the UTE μ-map and the T1-weighted (T1w) MR image in order to improve convergence towards a solution. Results show that the modified MLAA algorithm improved the estimated emission image compared to standard OSEM/UTE and OSEM/DIXON. In certain regions of the brain, in particular close to the skull and the air cavities, the modified MLAA algorithm generated less error than OSEM/UTE and OSEM/Dixon. The modified MLAA algorithm is able to compute an attenuation μ-map that is slightly more similar to the aligned CT μ-map than the UTE μ-map.

Authors’ Affiliations

Rigshospitalet, University of Copenhagen, Denmark
Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet Copenhagen, Denmark
University of Leuven, Belgium


© Benoit et al; licensee Springer. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.