A biomechanical model of soft tissue deformation, with applications to non-rigid registration of brain images with tumor pathology

Abstract

Abstract.The finite element method is applied to the biomechanics of brain tissue deformation. Emphasis is given to the deformations induced by the growth of tumors, and to the deformable registration of anatomical atlases with patient images. A uniform contraction of the tumor is first used to obtain an estimate of the shape of the brain prior to the growth of the tumor. A subsequent nonlinear regression method is used to improve on the above estimate. The resulting deformation mapping is finally applied to an atlas, yielding the registration of the atlas with the tumor-deformed anatomy. A preliminary 2D implementation that includes inhomogeneity and a nonlinear elastic material model is tested on simulated data as well as a patient image. The long-term scope of this work is its application to surgical planning systems.

Realistic simulation of the 3-D growth of brain tumors in MR images coupling diffusion with biomechanical deformation

“…However, because of the GTV1 inhomogeneity and because cells can be exchanged between the GTV1 and the GTV2, η does not directly characterize the GTV1 cells aggressiveness but represents an average volume expansion speed. As proposed in [32] we use a penalty method to impose this volume variation via a homogeneous pressure into the GTV1.…”

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images

“…As the deformation is only based on contours of interest, the probability of registration errors increases more we are far from these contours. As far as we know, most of the existing methods for registration of images with space-occupying tumors are either surface-based [10,12,15,35] or voxel-based [2,4,[6][7][8]36] approaches. However, in our opinion it is worth to study how to combine the advantages of both approaches.…”

Symmetrization of the Non-rigid Registration Problem Using Inversion-Invariant Energies: Application to Multiple Sclerosis

“…This includes the usual similarity energies and quadratic regularization energies such as linear elastic or thin plate energies. Even the general, non-linear elasticity is conceptually asymmetric since one of the images is supposed to be in a no-stress state and not the other; see [8] for an example showing the importance of this consideration.…”