Automatic Removal of Mechanical Fixations from CT Imagery with Particle Swarm Optimisation

Ryalat, Mohammad Hashem, Laycock, Stephen and Fisher, Mark (2017) Automatic Removal of Mechanical Fixations from CT Imagery with Particle Swarm Optimisation. In: Bioinformatics and Biomedical Engineering. Lecture Notes in Computer Science . Springer, ESP, pp. 419-431. ISBN 978-3-319-56147-9

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Abstract

Fixation devices are used in radiotherapy treatment of head and neck cancers to ensure successive treatment fractions are accurately targeted. Typical fixations usually take the form of a custom made mask that is clamped to the treatment couch and these are evident in many CT data sets as radiotherapy treatment is normally planned with the mask in place. But the fixations can make planning more difficult for certain tumor sites and are often unwanted by third parties wishing to reuse the data. Manually editing the CT images to remove the fixations is time consuming and error prone. This paper presents a fast and automatic approach that removes artifacts due to fixations in CT images without affecting pixel values representing tissue. The algorithm uses particle swarm optimisation to speed up the execution time and presents results from five CT data sets that show it achieves an average specificity of 92.01% and sensitivity of 99.39%.

Item Type:	Book Section
Uncontrolled Keywords:	immobilization mask,ct images,head and neck cancer,sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School:	Faculty of Science > School of Computing Sciences Faculty of Science
UEA Research Groups:	Faculty of Science > Research Groups > Interactive Graphics and Audio
Depositing User:	Pure Connector
Date Deposited:	21 Mar 2017 01:44
Last Modified:	20 Apr 2023 01:11
URI:	https://ueaeprints.uea.ac.uk/id/eprint/63046
DOI:	10.1007/978-3-319-56148-6_37

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