Authors:
Anja Frost
1
;
Eike Renners
1
and
Michael Hötter
2
Affiliations:
1
Institut für Innovationstransfer and University of Applied Sciences and Arts, Germany
;
2
Institut für Innovationstransfer an der Fachhochschule Hannover, Germany
Keyword(s):
Computer Tomography, CT, Discrete Tomography, DT, X-ray, Emission Data, Limited Data Problem, Three Dimensional Image Reconstruction, Algebraic Reconstruction Technique (ART), Binary Steering, Evaluation, Probability Calculus, Accuratio.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Geometry and Modeling
;
Image and Video Analysis
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
;
Image-Based Modeling
;
Pattern Recognition
;
Software Engineering
Abstract:
Computer Tomography is aimed to calculate a three dimensional reconstruction of the inside of an object from series of X-ray images. This calculation corresponds to the solution of a system of linear equations, in which the equations arise from the measured X-rays and the variables from the voxels of the reconstruction volume, or more precisely, their density values. Unfortunately, some applications do not supply enough equations. In that case, the system is underdetermined. The reconstructed object, as only estimated, seems to be stretched. As there are a few voxels, that are already representing the object true to original, it is possible to exclude these variables from the system of equations. Then, the number of variables decreases. Ideally, the system gets solvable. In this paper we concentrate on the detection of all good reconstructed voxels i.e. we introduce a quality measure, called Accuratio, to evaluate the volume voxel by voxel. In our experi-mental results we show the re
liability of Accuratio by applying it to an iterative reconstruction algorithm. In each iteration step the whole volume is evaluated, voxels with high Accuratio are excluded and the new system of equations is reconstructed again. Steadily the reconstructed object becomes “destretched”.
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