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Large scale tomographic reconstruction algorithm based on algebraic approach
Author(s): M. Chukalina; I. Polyakov; I. Terekhin; A. Ingacheva; A. Buzmakov; I. Yakimchuk; I. Varfolomeev; D. Nikolayev
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Paper Abstract

The present paper is devoted to the solution of a tomographic reconstruction problem of using a regularized algebraic approach for large scale data. The paper explores the issues related to the use of cone beam polychromatic computed tomography. An algorithm for regularized solution of the linear operator equation is described. The minimizing parametric composite function is given and step of the iterative procedure developed is written. The reconstructed volumetric image is about 60 billions voxels. It forces to divide the task of reconstruction of the full volume into subtasks for the efficient implementation of the reconstruction algorithm on the GPU. In each of the subtasks the current solution for the local volume of a given size is calculated. An approach to local volumes selection and solutions crosslinking is described. We compared the image quality of the proposed algorithm with results of Filtered Back Projection (FBP) algorithm.

Paper Details

Date Published: 15 March 2019
PDF: 6 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 1104109 (15 March 2019); doi: 10.1117/12.2522991
Show Author Affiliations
M. Chukalina, FSRC “Crystallography and Photonics” RAS (Russian Federation)
Institute for Information Transmission Problems (Russian Federation)
I. Polyakov, Institute for Information Transmission Problems (Russian Federation)
I. Terekhin, Institute for Information Transmission Problems (Russian Federation)
A. Ingacheva, Institute for Information Transmission Problems (Russian Federation)
A. Buzmakov, FSRC "Crystallography and Photonics" RAS (Russian Federation)
I. Yakimchuk, Schlumberger Moscow Research Ctr. (Russian Federation)
I. Varfolomeev, Schlumberger Moscow Research Ctr. (Russian Federation)
D. Nikolayev, Institute for Information Transmission Problems (Russian Federation)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

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