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A maximum likelihood approach to image reconstruction

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The article was published on 1976-01-01 and is currently open access. It has received 16 citations till now. The article focuses on the topics: Maximum likelihood sequence estimation & Expectation–maximization algorithm.

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Algorithms for limited-view computed tomography: an annotated bibliography and a challenge.

TL;DR: An overview of techniques proposed to tackle the problem of limited-view computed tomography, employing diverse theories such as signal recovery, image restoration, constrained deconvolution, and constrained optimization, as well as novel schemes such as iterative object-dependent algorithms incorporating a priori knowledge and use of multispectral radiation are presented.
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A Natural Pixel Decomposition for Two-Dimensional Image Reconstruction

TL;DR: In two-dimensional image reconstruction from line integrals using maximum likelihood, Bayesian, or minimum variance algorithms, the x-y plane on which the object estimate is defined is decomposed into nonoverlapping regions, or "pixels".
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A review on biomedical image processing and future trends.

TL;DR: A review on the current state-of-the-art techniques in biomedical image processing and comments on future trends are presented.
Journal ArticleDOI

A Maximum Likelihood Approach to Transmission Image Reconstruction from Projections

TL;DR: In this paper, the joint probability density function of the projections was used to derive the reconstruction scheme which is optimum in the maximum likelihood sense, and it was shown that for an average number of counts detected in excess of approximately 100 per projection, the image is essentially unbiased.

Penalized Weighted Least-Squares ImageReconstruction for Positron Emission Tomography

TL;DR: Qualitative results suggest that the streak artifacts common to the FBP method are nearly eliminated by the PWLS+SOR method, and indicate that the proposed method for weighting the measurements is a significant factor in the improvement over FBP.