Statistical models of shape and appearance are widely used for the analysis of biomedical images. Two deficiencies of these models is that they require annotation across a large number of images in order to be built and, having built such models, it is then difficult to reason about their validity or assess their quality. Herein, a method is described which addresses both problems and establish...

The use of functional imaging in radiotherapy treatment (RT) planning requires accurate co-registration of functional imaging scans to CT scans. We evaluated six methods of image registration for use in SPECT-guided radiotherapy treatment planning. Methods varied in complexity from 3D affine transform based on control points to diffeomorphic demons and level set non-rigid registration. Ten lung...

The Student's-t mixture model, which is heavily tailed and more robust than the Gaussian mixture model, has recently received great attention on image processing. In this paper, we propose a robust non-rigid point set registration algorithm using the Student's-t mixture model. Specifically, first, we consider the alignment of two point sets as a probability density estimation problem and treat ...

Non-rigid image registration (NIR) is an essential tool for morphologic comparisons in the presence of intraand inter-individual anatomic variations. Many NIRmethods have been developed, but are especially difficult to evaluate since point-wise inter-image correspondence is usually unknown, i.e., there is no “Gold Standard” to evaluate performance. The Non-rigid Image Registration Evaluation Pr...

We propose a new method for automatic 3D multimodal registration based on anatomical landmark detection. Landmark detectors are learned independantly in the two imaging modalities using Extremely Randomized Trees and multi-resolution voxel windows. A least-squares fitting algorithm is then used for rigid registration based on the landmark positions as predicted by these detectors in the two ima...

In order to combine preoperative data with intraoperative scans for image-guided neurosurgery visualization, accurate registration is necessary. It has been determined previously that a suitable way to model the non-rigid deformations due to brain shift is via a biomechanical model that treats the brain as a homogeneous, isotropic, linear elastic solid. This work extends that model-based non-ri...

ÐAccurate and robust correspondence calculations are very important in many medical and biological applications. Often, the correspondence calculation forms part of a rigid registration algorithm, but accurate correspondences are especially important for elastic registration algorithms and for quantifying changes over time. In this paper, a new correspondence calculation algorithm, CSM (Corresp...