X-ray mammogram registration: A novel validation method

Establishing spatial correspondence between features visible in x-ray mammograms obtained at different times has great potential to aid assessment of change in the breast and facilitate its quantification. The literature contains numerous non-rigid registration algorithms developed for this purpose, but quantitative estimation of registration accuracy is limited. We describe a novel validation method which simulates plausible mammographic compressions of the breast using all MRI derived finite element model. Known 3D displacements are projected into 2D and test images simulated from these same compressed MR volumes. In this way we call generate convincing images with known 2D displacements with which to validate a registration algorithm. We illustrate this approach by computing the accuracy for a non-rigid registration algorithm applied to mammograms simulated from three patient MR datasets

Medially based meshing with finite element analysis of prostate deformation

Abstract. The finite element method (FEM) is well suited for use in the non-rigid registration of magnetic resonance spectroscopy images (MRSI) with intraoperative ultrasound images of the prostate because FEM provides a principled method for modeling the physical deformation caused when the MRSI intra-rectal imaging probe compresses the prostate. However, FEM requires significant labor and computational time to construct a finite element model and solve the resulting large system of equations. In particular, any finite element based registration method must address the questions of how to generate a mesh from an image and how to solve the system of finite element equations efficiently. This paper focuses on how m-rep image segmentations can be used to generate high quality multi-scale hexahedral meshes for use with FEM. Results from the application of this method to the registration of CT images of a prostate phantom with implanted brachytherapy seeds are presented.