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

Mohammad Hashem Ryalat, Stephen Laycock, Mark Fisher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)
11 Downloads (Pure)


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.
Original languageEnglish
Title of host publication2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)
PublisherThe Institute of Electrical and Electronics Engineers (IEEE)
Publication statusPublished - 13 Apr 2017
Event2017 IEEE International Conference on Biomedical and Health Informatics - Orlanda, United States
Duration: 16 Feb 201719 Feb 2017


Conference2017 IEEE International Conference on Biomedical and Health Informatics
Country/TerritoryUnited States


  • Immobilisation Mask
  • CT Images
  • Head and Neck Cancer

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