A Novel Non-Rigid Registration Approach for Accurate Quantification of Dynamic Contrast Enhanced MR Imaging (DCEMRI) in Ovary Employing Residual Complexity Framework

Abstract

Typically, quantification of DCE-MRI of ovary is susceptible to errors caused by motion artifacts and intensity inhomogeneity induced by bias fields. Motion artifacts and bias fields introduce signal intensity variations in the images that must be resolved from intensity changes caused by the passage of contrast agent. Thus, registration of DCE-MRI image sequence is a challenging issue. In this work, we proposed a solution to the misregistration problem of DCE-MR images, by exploiting residual complexity (RC) similarity measure, to account for complex intensity variations in a non-rigid registration approach and for precise quantification of DCE-MRI to characterize ovarian masses.