2007/05/18 by Ali Mohammad‐Djafari, Mohammad-Djafari, Ali
Computer Science · Medicine · #Computational Physics (physics.comp-ph) #Data Analysis #Digital Image Processing Techniques #FOS: Physical sciences #Medical Image Segmentation Techniques #Medical Imaging Techniques and Applications #Statistics and Probability (physics.data-an)
paper · pdf · doi:10.48550/arxiv.0705.2698
openalex publication_date 2007/05/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
English: This paper concerns the image reconstruction from a few projections in Computed Tomography (CT). The main objective of this paper is to show that the problem is so ill posed that no classical method, such as analytical methods based on inverse Radon transform, nor the algebraic methods such as Least squares (LS) or regularization theory can give satisfactory result. As an example, we consider in detail the case of image reconstruction from two horizontal and vertical projections. We then show how a particular composite Markov modeling and the Bayesian estimation framework can possibly propose satisfactory solutions to the problem. For demonstration and educational purpose a set of Matlab programs are given for a live presentation of the results. ----- French: Ce travail, à but pédagogique, présente le problème inverse de la reconstruction d'image en tomographie X lorsque le nombre des projections est très limité. voir le texte en Anglais et en Français.