A fast and automatic approach for removing artefacts due to immobilisation masks in X-ray CT

Ryalat, Mohammad Hashem, Laycock, Stephen and Fisher, Mark (2017) A fast and automatic approach for removing artefacts due to immobilisation masks in X-ray CT. In: 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI). The Institute of Electrical and Electronics Engineers (IEEE), USA.

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Immobilisation masks are fixation devices that are used when administering radiotherapy treatment to patients with tumours affecting the head and neck. Radiotherapy planning X-ray Computer Tomography (CT) data sets for these patients are captured with the immobilisation mask fitted and manually editing the X-ray CT images to remove artefacts due to the mask is time consuming and error prone. This paper represents the first study that employs a fast and automatic approach to remove image artefacts due to masks in X-ray CT images without affecting pixel values representing tissue. Our algorithm uses a fractional order Darwinian particle swarm optimisation of Otsu’s method combined with morphological post-processing to classify pixels belonging to the mask. The proposed approach is tested on five X-ray CT data sets and achieves an average specificity of 92.01% and sensitivity of 99.39%. We also present results demonstrating the comparative speed-up obtained by fractional order Darwinian particle swarm optimisation.

Item Type: Book Section
Uncontrolled Keywords: immobilisation 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: 22 Mar 2017 01:41
Last Modified: 19 Apr 2023 20:35
URI: https://ueaeprints.uea.ac.uk/id/eprint/63057
DOI: 10.1109/BHI.2017.7897198


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