ML-reconstruction for TOF-PET with Simultaneous Estimation of the Attenuation Factors

Ahmadreza Rezaei, Michel Defrise, Johan Nuyts

Research output: Contribution to journalArticlepeer-review

90 Citations (Scopus)


In positron emission tomography (PET), attenuation correction is typically done based on information obtained from transmission tomography. Recent studies show that time-of-flight (TOF) PET emission data allow joint estimation of activity and attenuation images. Mathematical analysis revealed that the joint estimation problem is determined up to a scale factor. In this work, we propose a maximum likelihood reconstruction algorithm that jointly estimates the activity image together with the sinogram of the attenuation factors. The algorithm is evaluated with 2D and 3D simulations as well as clinical TOF-PET measurements of a patient scan and compared to reference reconstructions. The robustness of the algorithm to possible imperfect scanner calibration is demonstrated with reconstructions of the patient scan ignoring the varying detector sensitivities.
Original languageEnglish
Pages (from-to)1563-1572
Number of pages10
JournalIEEE Transactions on Medical Imaging
Publication statusPublished - 2014


  • positron emission tomography
  • time-of-flight
  • image reconstruction


Dive into the research topics of 'ML-reconstruction for TOF-PET with Simultaneous Estimation of the Attenuation Factors'. Together they form a unique fingerprint.

Cite this