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Automated processing pipeline for texture analysis of childhood brain tumours based on multimodal magnetic resonance imaging
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Tantisatirapong, Suchada, Davies, Nigel P., Abernethy, Lawrence, Auer, Dorothee P., Clark, Chris A., Grundy, Richard, Jaspan, Tim, Hargrave, Darren, MacPherson, Lesley, Leach, Martin O., Payne, Geoff S., Pizer, Barry L., Peet, Andrew C. and Arvanitis, Theodoros N. (2013) Automated processing pipeline for texture analysis of childhood brain tumours based on multimodal magnetic resonance imaging. In: BioMed 2013, Innsbruck, Austria, 13–15 Feb 2013. Published in: Proceedings of the IASTED International Conference on Biomedical Engineering pp. 376-383. doi:10.2316/P.2013.791-081
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Official URL: http://dx.doi.org/10.2316/P.2013.791-081
Abstract
Primary brain tumours are the most common solid tumours found in children and are an important cause of morbidity and mortality. Magnetic resonance imaging (MRI) is commonly used for non-invasive early-detection, diagnosis, delineation of tumours for treatment planning and assessment of post treatment changes. Different MRI modalities provide complementary contrast of tumour tissues, which can have varying degrees of heterogeneity and diffusivity in different tumour types. A variety of texture analysis methods have been shown to reveal tumour histological types. It is hypothesized that textural features, based on conventional and diffusion MRI modalities, would differentiate the characteristics of tumours. Tumour extraction is also a significant procedure needed to obtain a true tumour region. Semi-automated segmentation methods were applied, in comparison with the gold standard of manual segmentation by an expert, in order to speed up a manual segmentation approach and reduce any bias effects. In this study, we present an automatic processing pipeline for the characterization of brain tumours, based on texture analysis. We apply this to a multi-centre dataset of paediatric brain tumours and investigate the accuracy of tumour classification, based on textural features of diffusion and conventional MR images.
| Item Type: | Conference Item (Paper) | ||||
|---|---|---|---|---|---|
| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | ||||
| Journal or Publication Title: | Proceedings of the IASTED International Conference on Biomedical Engineering | ||||
| Book Title: | Biomedical Engineering | ||||
| Official Date: | 2013 | ||||
| Dates: |
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| Page Range: | pp. 376-383 | ||||
| DOI: | 10.2316/P.2013.791-081 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Conference Paper Type: | Paper | ||||
| Title of Event: | BioMed 2013 | ||||
| Type of Event: | Conference | ||||
| Location of Event: | Innsbruck, Austria | ||||
| Date(s) of Event: | 13–15 Feb 2013 |
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