A combined algorithm for breast MRI motion correction

Abstract

Correction of patient motion is a fundamental preprocessing step for dynamic contrast-enhanced (DCE) breast MRI, removing artifacts induced by involuntary movement and facilitating quantitative analysis of contrast agent kinetics. Image registration algorithms commonly employed for this task align subsequent temporal images of the dynamic MRI by maximizing intensity-, correlation- or entropy-based similarity measures between image pairs. To compensate for global patient motion, frequently an initial affine linear or rigid transformation is estimated. Subsequently, local image variablity is reduced by maximizing local similarity measures and using viscous fluid or elastic regularization terms. We present a novel iterative scheme combining local and global registration into one single algorithm, limiting computational overhead, reducing interpolation artifacts and generally improving the quality of registration results. The relation between local and global motion is adjusted by the introduction of corresponding flexible weighting functions, allowing for a sound combination of both registration types and a potentially wider range of computable transformations. The proposed method is evaluated on both synthetic images and clinical breast MRI data. The results demonstrate that our method works stable and reliably compensates for common motion artifacts typical to DCE MR mammography.