A fast approach to segmentation of PET brain images for extraction of features
Gao, Xiaohong W. and Clark, John (2008) A fast approach to segmentation of PET brain images for extraction of features. In: Medical imaging and informatics. Gao, Xiaohong W. and Loomes, Martin J. and Comley, Richard A. and Muller, Henning and Luo, Shuqian, eds. Lecture Notes in Computer Science (4987). Springer, Berlin, pp. 197-206. ISBN 3794521935
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Position Emission Tomography (PET) is increasingly applied in the diagnosis and surgery in patients thanks to its ability of showing nearly all types of lesions including tumour and head injury. However, due to its natures of low resolution and different appearances as a result of different tracers, segmentation of lesions presents great challenges. In this study, a simple and robust algorithm is proposed via additive colour mixture approach. Comparison with the other two methods including Bayesian classified and geodesic active contour is also performed, demonstrating the proposed colouring approach has many advantages in terms of speed, robustness, and user intervention. This research has many medical applications including pharmaceutical trials, decision making for drug treatment or surgery and patients follow-up and shows potential to the development of content-based image databases when coming to characterise PET images using lesion features.
|Item Type:||Book Section|
|Additional Information:||2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007.|
|Research Areas:||A. > School of Science and Technology > Computer Science > Artificial Intelligence group
A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer and Communications Engineering
A. > School of Science and Technology > Computer Science > SensoLab group
|Depositing User:||Repository team|
|Date Deposited:||01 Apr 2009 10:07|
|Last Modified:||15 Feb 2016 15:05|
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