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Binary Tomography Reconstruction by Particle Aggregation

Binary Tomography Reconstruction by Particle Aggregation

Al-Rifaie, Mohammad Majid ORCID: 0000-0002-1798-9615 and Blackwell, Tim (2016) Binary Tomography Reconstruction by Particle Aggregation. In: Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 -- April 1, 2016, Proceedings, Part I. Lecture Notes in Computer Science, 9597 . Springer, Cham, Switzerland, pp. 754-769. ISBN 978-3319312033 ISSN 0302-9743 (Print), 1611-3349 (Online) (doi:https://doi.org/10.1007/978-3-319-31204-0_48)

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Abstract

This paper presents a novel reconstruction algorithm for bi- nary tomography based on the movement of particles. Particle Aggregate Reconstruction Technique (PART) supposes that pixel values are particles, and that the particles can diffuse through the image, sticking together in regions of uniform pixel value known as aggregates. The algorithm is tested on four phantoms of varying sizes and numbers of forward projections and compared to a random search algorithm and to SART, a standard algebraic reconstruction method. PART, in this small study, is shown to be capable of zero error reconstruction and compares favourably with SART and random search.

Item Type: Conference Proceedings
Title of Proceedings: Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 -- April 1, 2016, Proceedings, Part I
Uncontrolled Keywords: Binary tomography, discrete tomography, particle aggregation, underdetermined linear systems
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Computing & Information Systems
Last Modified: 12 Jul 2019 11:58
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/20997

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