Propagation of errors from the sensitivity image in list mode reconstruction

• Published in: IEEE transactions on medical imaging Vol. 23; no. 9; pp. 1094 - 1099
• Main Authors: Jinyi Qi, Huesman, R.H.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.09.2004; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Attenuation; Computer errors; Computer Simulation; Data Interpretation, Statistical; Detectors; Error analysis; Frequency; Image analysis; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image reconstruction; Information Storage and Retrieval - methods; Likelihood Functions; Models, Theoretical; Object detection; Reproducibility of Results; Sensitivity and Specificity; Studies; Taylor series
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2004.829333

List mode image reconstruction is attracting renewed attention. It eliminates the storage of empty sinogram bins. However, a single back projection of all LORs is still necessary for the pre-calculation of a sensitivity image. Since the detection sensitivity is dependent on the object attenuation and detector efficiency, it must be computed for each study. Exact computation of the sensitivity image can be a daunting task for modern scanners with huge numbers of LORs. Thus, some fast approximate calculation may be desirable. In this paper, we analyze the error propagation from the sensitivity image into the reconstructed image. The theoretical analysis is based on the fixed point condition of the list mode reconstruction. The nonnegativity constraint is modeled using the Kuhn-Tucker condition. With certain assumptions and the first-order Taylor series approximation, we derive a closed form expression for the error in the reconstructed image as a function of the error in the sensitivity image. The result shows that the error response is frequency-dependent and provides a simple expression for determining the required accuracy of the sensitivity image calculation. Computer simulations show that the theoretical results are in good agreement with the measured results.