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Автор D W Wilson
Автор B M W Tsui
Автор H H Barrett
Дата выпуска 1994-05-01
dc.description For pt.I see ibid., vol.39, no.5, p.833-46 (1994). In pt.I the authors derived a theoretical formulation for estimating the statistical properties of images reconstructed using the iterative maximum-likelihood expectation-maximization (ML-EM) algorithm. To gain insight into this complex problem, two levels of approximation were considered in the theory. These techniques revealed the dependence of the variance and covariance of the reconstructed image noise on the source distribution, imaging system transfer function, and iteration number. Here, a Monte Carlo approach was taken to study the noise properties of the ML-EM algorithm and to test the predictions of the theory. The study also served to evaluate the approximations used in the theory. Simulated data from phantoms were used in the Monte Carlo experiments. The ML-EM statistical properties were calculated from sample averages of a large number of images with different noise realizations. The agreement between the more exact form of the theoretical formulation and the Monte Carlo formulation was better than 10% in most cases examined, and for many situations the agreement was within the expected error of the Monte Carlo experiments. Results from the studies provide valuable information about the noise characteristics of ML-EM reconstructed images. Furthermore, the studies demonstrate the power of the theoretical and Monte Carlo approaches for investigating noise properties of statistical reconstruction algorithms.
Формат application.pdf
Издатель Institute of Physics Publishing
Название Noise properties of the EM algorithm. II. Monte Carlo simulations
Тип paper
DOI 10.1088/0031-9155/39/5/005
Electronic ISSN 1361-6560
Print ISSN 0031-9155
Журнал Physics in Medicine and Biology
Том 39
Первая страница 847
Последняя страница 871
Аффилиация D W Wilson; Dept. of Biomed. Eng., North Carolina Univ., Chapel Hill, NC, USA
Аффилиация B M W Tsui; Dept. of Biomed. Eng., North Carolina Univ., Chapel Hill, NC, USA
Аффилиация H H Barrett; Dept. of Biomed. Eng., North Carolina Univ., Chapel Hill, NC, USA
Выпуск 5

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