Citations:MLEM

English citations of MLEM

• 2006, Martin Charron, Pediatric PET Imaging, Springer Science & Business Media (→ISBN), 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), 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), 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), 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), 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 ...