Abstract
Contouring of the target and risk anatomy is one of the most time consuming procedures in radiotherapy planning (RTP). The main imaging modality used in RTP is the computer tomography (CT), where the application of automated segmentation methods in certain treatment areas, such as head and neck, is difficult due to insufficient soft tissue contrast. Magnetic resonance imaging (MRI) generates images with better soft tissue contrast, and it is expected that MRI will be more extensively used in RTP. Owing to the image formation principles, the feature variability of MR data is much higher compared to CT. In this paper, we present an approach that combines a model- based segmentation method with the pattern classification framework to segment organs in MR images of the head and neck area. A validation study demonstrates that the proposed approach is feasible for the organs tested.
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© 2005 Springer-Verlag Berlin Heidelberg
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Bacher, M.G., Pekar, V., Kaus, M.R. (2005). Model-Based Segmentation of Anatomical Structures in MR Images of the Head and Neck Area. In: Meinzer, HP., Handels, H., Horsch, A., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2005. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-26431-0_24
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DOI: https://doi.org/10.1007/3-540-26431-0_24
Publisher Name: Springer, Berlin, Heidelberg
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