Citations:MLEM


 * 2006, Martin Charron, Pediatric PET Imaging, Springer Science & Business Media (ISBN 9780387346410), page 163:
 * probable value of the image vector F for the measured projection P. For example, the MLEM algorithm was designed to maximize the posterior probability of the reconstructed image for a given projection data with Poisson statistics, ...
 * 2019, Ehsan Samei, Donald J. Peck, Hendee's Physics of Medical Imaging, John Wiley & Sons (ISBN 9781118671061), page 288:
 * A common method used for iterative reconstruction in emission tomography is the maximum likelihood expectation maximization (MLEM) algorithm [6]. This method seeks to reconstruct the object “most likely” in a statistical sense to have ...
 * 2009, Gabrielle Allen, Jaroslaw Nabrzyski, Edward Seidel, Geert Dick van Albada, Jack Dongarra, Peter M.A. Sloot, Computational Science – ICCS 2009: 9th International Conference Baton Rouge, LA, USA, May 25-27, 2009 Proceedings, Part I, Springer (ISBN 9783642019708), page 493:
 * A comprehensive overview of iterative algorithms for image reconstruction in general is given in [7]. ... Algorithm. The MLEM algorithm was first proposed by Shepp and Vardi [11]. It can be viewed as an implementation of the more ...
 * 2013, C. Schiepers, Diagnostic Nuclear Medicine, Springer Science & Business Media (ISBN 9783662065907), page 239:
 * In every iteration the algorithm checks the current estimate and improves it based on that evaluation. A key feature of iterative ... In fact, this is the main difference between MLEM and other iterative reconstruction algorithms.
 * 2016, Kristen M. Waterstram-Rich, David Gilmore, Nuclear Medicine and PET/CT - E-Book: Technology and Techniques, Elsevier Health Sciences (ISBN 9780323400350), page 276:
 * The MLEM algorithm converges slowly, requiring many more iterations than iterative FBP algorithms; however, the slowly converging characteristics of this algorithm yield greater control over image noise.19,29 The point of convergence of ...