Skip to main navigation Skip to search Skip to main content

Polar Bear Optimization For Industrial Computed Tomography With Incomplete Data

  • Warsaw University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

In this article, Polar Bear Optimization Algorithm (PBO) is parallelized to solve the problem of computed tomography (CT) with incomplete data. It is vary hard to model correctly 2D and 3D objects by using CT scanners when information is incomplete. Our approach is to use PBO to reduce recovery time and simplify specificity of the phenomenon. Results from our research show that proposed approach is enabling fast and accurate reconstruction of objects modeled in projection space.

Original languageEnglish
Title of host publication2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages681-687
Number of pages7
ISBN (Electronic)9781728183923
DOIs
Publication statusPublished - 2021
Event2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Virtual, Online, Poland
Duration: 28 Jun 20211 Jul 2021

Publication series

Name2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings

Conference

Conference2021 IEEE Congress on Evolutionary Computation, CEC 2021
Country/TerritoryPoland
CityVirtual, Online
Period28/06/211/07/21

Keywords

  • Computed tomography
  • Heuristics
  • Incomplete data
  • Parallel computing
  • Polar bear optimization

ASJC Scopus subject areas

  • Modeling and Simulation
  • Computational Mathematics

Fingerprint

Dive into the research topics of 'Polar Bear Optimization For Industrial Computed Tomography With Incomplete Data'. Together they form a unique fingerprint.

Cite this