Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

Bauer, Stefan; Nolte, Lutz-Peter; Reyes, Mauricio (2011). Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model. In: ISBI'11: Proceedings of the 2011 IEEE international conference on Biomedical imaging (pp. 2018-2021). IEEE Press 10.1109/ISBI.2011.5872808

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We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

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