Title :
Study of the convergence properties of the updating coefficients in the EM algorithm for PET
Author :
Kontaxakis, George ; Tzanakos, G.
Author_Institution :
Dept. of Biomed. Eng., Rutgers Univ., Piscataway, NJ, USA
Abstract :
The authors have performed a series of simulation studies of the expectation maximization (EM) algorithm, using the Hoffman Brain Phantom. They investigated the problem of image deterioration after the iterative procedure has been carried out for an excessive number of iterations and they have studied the convergence characteristics of the updating coefficients in this algorithm. These coefficients can provide a normalized to unity projection of the reconstructed image vectors and valuable information (added noise, location of pixels etc.) can be extracted from their statistical properties. A stopping criterion can also be extracted based on the results of this study
Keywords :
algorithm theory; brain; image reconstruction; iterative methods; medical image processing; positron emission tomography; EM algorithm; Hoffman Brain Phantom; PET; convergence properties; image deterioration; iterative procedure; medical diagnostic imaging; nuclear medicine; pixels location; reconstructed image vectors; statistical properties; stopping criterion; unity projection; updating coefficients; Brain modeling; Convergence; Data mining; Histograms; Image quality; Image reconstruction; Imaging phantoms; Iterative algorithms; Maximum likelihood detection; Pixel; Positron emission tomography;
Conference_Titel :
Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-2050-6
DOI :
10.1109/IEMBS.1994.411835
