Presentation + Paper
3 October 2016 Proposal of fault-tolerant tomographic image reconstruction
Hiroyuki Kudo, Keita Takaki, Fukashi Yamazaki, Takuya Nemoto
Author Affiliations +
Abstract
This paper deals with tomographic image reconstruction under the situation where some of projection data bins are contaminated with abnormal data. Such situations occur in various instances of tomography. We propose a new reconstruction algorithm called the Fault-Tolerant reconstruction outlined as follows. The least-squares (L2- norm) error function || Ax- b||22 used in ordinary iterative reconstructions is sensitive to the existence of abnormal data. The proposed algorithm utilizes the L1-norm error function || Ax- b||11 instead of the L2-norm, and we develop a row-action-type iterative algorithm using the proximal splitting framework in convex optimization fields. We also propose an improved version of the L1-norm reconstruction called the L1-TV reconstruction, in which a weak Total Variation (TV) penalty is added to the cost function. Simulation results demonstrate that reconstructed images with the L2-norm were severely damaged by the effect of abnormal bins, whereas images with the L1-norm and L1-TV reconstructions were robust to the existence of abnormal bins.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hiroyuki Kudo, Keita Takaki, Fukashi Yamazaki, and Takuya Nemoto "Proposal of fault-tolerant tomographic image reconstruction", Proc. SPIE 9967, Developments in X-Ray Tomography X, 99671K (3 October 2016); https://doi.org/10.1117/12.2237107
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Reconstruction algorithms

Evolutionary algorithms

Image restoration

Tomography

Algorithm development

Bismuth

Sensors

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