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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Automatic Removal of Mechanical Fixations from CT Imagery with Particle Swarm Optimisation
verfasst von : Mohammad Hashem Ryalat, Stephen Laycock, Mark Fisher
Erschienen in: Bioinformatics and Biomedical Engineering
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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%.