Mutual information based three-dimensional registration of rat brain magnetic resonance imaging time-series

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.

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► An efficient MI based registration method is proposed to align the rat brain tissues in MRI time-series.
► The combination of graph-based segmentation and atlas-based segmentation methods is proposed to segment rat brain.
► A two-stage registration framework including both deformable and rigid registration is used.
► The performance of MI as similarity metric is evaluated by analyzing its robustness to local intensity variation.
► Extensive experiments show that higher accuracy and reliability are acquired by our method than several other methods.