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

S Bauer, LP Nolte, M Reyes - 2011 IEEE International …, 2011 - ieeexplore.ieee.org
S Bauer, LP Nolte, M Reyes
2011 IEEE International Symposium on Biomedical Imaging: From Nano …, 2011ieeexplore.ieee.org
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 …
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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