Multimodal Elastic Matching of Brain Images

This paper presents an original method for three-dimensional elastic registration of multimodal images. We propose to make use of a scheme that iterates between correcting for intensity differences between images and performing standard monomodal registration. The core of our contribution resides in providing a method that finds the transformation that maps the intensities of one image to those of another. It makes the assumption that there are at most two functional dependences between the intensities of structures present in the images to register, and relies on robust estimation techniques to evaluate these functions. We provide results showing successful registration between several imaging modalities involving segmentations, T1 magnetic resonance (MR), T2 MR, proton density (PD) MR and computed tomography (CT).

• Type: Conference
• Year: 2000
• Where: ECCV
• Authors: Alexis Roche, Alexandre Guimond, Nicholas Ayache, Jean Meunier
• Keywords: Computer Vision, ECCV 2000, Modalities Involving Segmentations, Multimodal Images, Robust Estimation Techniques, Standard Monomodal Registration, Three-dimensional Elastic Registration