We propose volume registration procedures based on spherical artificial markers presented in medical multimodal data sets (MRI and CT, especially). The procedures proposed are either semi-automatic or fully-automatic. A semi-automatic approach requires to label approximate locations of the spherical markers in the data sets and then registration operates autonomically. A fully-automatic approac...

Image Registration is central to different applications such as medical analysis, biomedical systems, image guidance, etc. In this paper we propose a new algorithm for multimodal image registration. A Bayesian formulation is presented in which a likelihood term is defined using an observation model based on coefficient and geometric fields. These coefficients, that represent the local intensity...

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...

Nanoscale secondary ion mass spectrometry (nanoSIMS) and fluorescence in situ hybridization (FISH) microscopy provide high-resolution, multimodal image representations of the identity cell activity respectively targeted microbial communities microbiological research. Despite its importance to microbiologists, registration FISH nanoSIMS images is challenging given morphological distortion backgr...