Atlas Chordoma Neoplasm Image Based Modeling of Labeled Brain Tumor

The Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish the correspondence among a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown-up in the atlas based on a new multiscale, multiphysics model together with growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can function directly on the image voxelmesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method bids opportunities in atlas-based segmentation of tumorbearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression. Keywords—: Brain tumor, glioma, image analysis, tumor biomechanics, tumor growth modeling.