Summary
This paper presents a segmentation method of 3D time-series images for radiotherapy planning. The aim of this study is to propose some techniques for the segmentation of tumors surrounding or contained in the lungs. The 4D images are produced using a respiration gating procedure and computed tomography. The aim of the segmentation is to follow the tumor movement while the patient is breathing, so that he does not need to hold his respiration during the radiation treatment. The proposed technique is based on mathematical morphology and graph cuts. It uses a 4D watershed algorithm, combined with graph-based techniques to delineate the tumors in the time-series. The differences between different classical spatio-temporal segmentation algorithms will be highlighted, and conclusions on the related trade-offs between speed and precision will be drawn.
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Stawiaski, J., Decencière, E., Bidault, F. (2010). Spatio-Temporal Segmentation for Radiotherapy Planning. In: Fitt, A., Norbury, J., Ockendon, H., Wilson, E. (eds) Progress in Industrial Mathematics at ECMI 2008. Mathematics in Industry(), vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12110-4_31
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DOI: https://doi.org/10.1007/978-3-642-12110-4_31
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