Evaluation of control point selection in automatic, mutual information driven, 3D warping

Abstract

We have implemented automatic 3D thin-plate spline warping as a geometric interpolant to map one dataset volume onto another. Homologous control points in one space are iteratively moved by an optimizer to maximize the global mutual information between the two data volumes. Given two different poses between highly deformed objects we desire to compute the relative geometric deformation using a minimal set of control points as determined by number and placement. The general solution to this problem is not known. In this paper we assess retrospective control point selection for the case of significant patient motion during MRI breast imaging.