ML-Reconstruction for TOF-PET With Simultaneous Estimation of the Attenuation Factors

• Published in: IEEE transactions on medical imaging Vol. 33; no. 7; pp. 1563 - 1572
• Main Authors: Rezaei, Ahmadreza, Defrise, Michel, Nuyts, Johan
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Attenuation; Detectors; Humans; Image Processing, Computer-Assisted - methods; Image reconstruction; Joint activity and attenuation estimation; maximum likelihood; Noise; Phantoms, Imaging; Positron emission tomography; Positron-Emission Tomography - methods; self-normalization; Sensitivity; Thorax - diagnostic imaging; Three-dimensional displays; time-of-flight (TOF) positron emission tomography (PET)
• ISSN: 0278-0062; 1558-254X; 1558-254X
• DOI: 10.1109/TMI.2014.2318175

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 2-D and 3-D 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.