Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery

Bauer, Stefan; Lu, Huanxiang; May, Christian P.; Nolte, Lutz-P.; Büchler, Philippe; Reyes, Mauricio (2013). Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery. International journal of imaging systems and technology, 23(1), pp. 59-63. John Wiley & Sons 10.1002/ima.22037

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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 correspondence between 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 in the atlas based on a new multi-scale, multi-physics model including 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 operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Item Type:

Journal Article (Original Article)


04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued]

UniBE Contributor:

Bauer, Stefan; Lu, Huanxiang; May, Christian; Nolte, Lutz-Peter; Büchler, Philippe and Reyes, Mauricio


500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
000 Computer science, knowledge & systems




John Wiley & Sons




Mauricio Antonio Reyes Aguirre

Date Deposited:

15 Apr 2014 10:58

Last Modified:

27 Jan 2015 10:42

Publisher DOI:


Uncontrolled Keywords:

brain tumor, glioma, atlas-based segmentation, tumor-growth modeling, multimodal image analysis




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