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Computational and Mathematical Methods in Medicine
Volume 2015, Article ID 494691, 9 pages
Research Article

Adaptive Autoregressive Model for Reduction of Noise in SPECT

1Division of Nuclear Medicine, Department of Diagnostic Radiology, Oulu University Hospital (OYS), P.O. Box 500, 90029 Oulu, Finland
2Department of Automation Science and Engineering, Tampere University of Technology, P.O. Box 692, 33101 Tampere, Finland
3Joint Authority for Päijät-Häme Social and Health Care, Department of Clinical Physiology and Nuclear Medicine, Keskussairaalankatu 7, 15850 Lahti, Finland

Received 2 September 2014; Revised 5 November 2014; Accepted 2 December 2014

Academic Editor: Liang Li

Copyright © 2015 Reijo Takalo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents improved autoregressive modelling (AR) to reduce noise in SPECT images. An AR filter was applied to prefilter projection images and postfilter ordered subset expectation maximisation (OSEM) reconstruction images (AR-OSEM-AR method). The performance of this method was compared with filtered back projection (FBP) preceded by Butterworth filtering (BW-FBP method) and the OSEM reconstruction method followed by Butterworth filtering (OSEM-BW method). A mathematical cylinder phantom was used for the study. It consisted of hot and cold objects. The tests were performed using three simulated SPECT datasets. Image quality was assessed by means of the percentage contrast resolution (CR%) and the full width at half maximum (FWHM) of the line spread functions of the cylinders. The BW-FBP method showed the highest CR% values and the AR-OSEM-AR method gave the lowest CR% values for cold stacks. In the analysis of hot stacks, the BW-FBP method had higher CR% values than the OSEM-BW method. The BW-FBP method exhibited the lowest FWHM values for cold stacks and the AR-OSEM-AR method for hot stacks. In conclusion, the AR-OSEM-AR method is a feasible way to remove noise from SPECT images. It has good spatial resolution for hot objects.