Maximum Entropy And The Concept Of Feasibility In Tomographic Image Reconstruction

Jorge Nunez; Jorge Llacer

doi:10.1117/12.953221

1 May 1989 Maximum Entropy And The Concept Of Feasibility In Tomographic Image Reconstruction

Jorge Nunez, Jorge Llacer

Proceedings Volume 1090, Medical Imaging III: Image Formation; (1989) https://doi.org/10.1117/12.953221
Event: Medical Imaging III, 1989, Newport Beach, CA, United States

Abstract

Feasible images in tomographic image reconstruction are defined as those images compatible with the data by consideration of the statistical process that governs the physics of the problem. The first part of this paper reviews the concept of image feasibility, discusses its theoretical problems and practical advantages, and presents an assumption justifying the method and some preliminary results supporting it. In the second part of the paper two different algorithms for tomographic image reconstruction are developed. The first is a Maximum Entropy algorithm and the second is a full Bayesian algorithm. Both algorithms are tested for feasibility of the resulting images and we show that the Bayesian method yields feasible reconstructions in Positron Emission Tomography.

Citation Download Citation

Jorge Nunez and Jorge Llacer "Maximum Entropy And The Concept Of Feasibility In Tomographic Image Reconstruction", Proc. SPIE 1090, Medical Imaging III: Image Formation, (1 May 1989); https://doi.org/10.1117/12.953221

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