Colorectal MRI image registration using phase mutual information from non-parametric probability density function estimator

We propose a nonrigid registration algorithm and apply it to align pre- and post-chemotherapy colorectal MRI images. The algorithm combines feature-based and intensity-based image registration methods. We use local phase, as computed by monogenic signal, as the feature descriptor, and as the similarity measure in the registration algorithm, phase mutual information, which is estimated using NP windows, a non-parametric probability density function (PDF) estimator. Local deformations are modeled using the polyaffine transformation, which guarantees a smooth and invertible warping toward high image resolution. The algorithm is implemented in an adaptive manner, which makes the registration efficient and reliable. We show encouraging preliminary results and will include a performance evaluation on fives of cases in the final paper.