Alignment by Maximization of Mutual Information
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Random Walks for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
FLIRT with Rigidity--Image Registration with a Local Non-rigidity Penalty
International Journal of Computer Vision
Adaptive Stochastic Gradient Descent Optimisation for Image Registration
International Journal of Computer Vision
Registration of dynamic contrast enhanced MRI with local rigidity constraint
WBIR'12 Proceedings of the 5th international conference on Biomedical Image Registration
Hi-index | 0.00 |
An efficient mutual information (MI) based automatic registration method is introduced to align the rat brain tissues in magnetic resonance imaging (MRI) time-series, which is critical to the MRI tracer method for quantitative analysis of brain extracellular space (ECS). The method is specially designed to address the specific properties of contrast-enhanced MRI time-series. Firstly, a segmentation method is proposed to extract the brain tissue mask which is used in MI computing to avoid the adverse effects of surrounding deformed tissues. Secondly, a two-stage registration framework is proposed, where the images are first aligned using deformable registration and then finally matched by rigid registration. A series of experiments are conducted to evaluate the registration method qualitatively and quantitatively. The experimental results show that the proposed method has a high degree of accuracy and reliability, and is adequate to the task of three-dimensional registration of rat brain MRI time-series.