Abstract
In cancer treatment, understanding the aggressiveness of the tumor is essential in therapy planning and patient follow-up. In this article, we present a novel method for quantifying the speed of invasion of gliomas in white and grey matter from time series of magnetic resonance (MR) images. The proposed approach is based on mathematical tumor growth models using the reaction-diffusion formalism. The quantification process is formulated by an inverse problem and solved using anisotropic fast marching method yielding an efficient algorithm. It is tested on a few images to get a first proof of concept with promising new results.
This work has been partly supported by the European Health-e-Child project (IST-2004-027749) and by the CompuTumor project (http://www-sop.inria.fr/ asclepios/projects/boston/).
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Konukoglu, E., Clatz, O., Bondiau, PY., Sermesant, M., Delingette, H., Ayache, N. (2007). Towards an Identification of Tumor Growth Parameters from Time Series of Images. In: Ayache, N., Ourselin, S., Maeder, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. MICCAI 2007. Lecture Notes in Computer Science, vol 4791. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75757-3_67
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DOI: https://doi.org/10.1007/978-3-540-75757-3_67
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