Dynamic contrast-enhanced magnetic resonance imaging studies of the breast are frequently degraded by patient motion. In order to correct for this, any registration algorithm must overcome two major challenges: the highly deformable nature of the breast itself and the need to remove changes in signal intensity due to patient motion whilst leaving potentially significant changes in signal intensity due to changes in contrast agent concentration unchanged. In this paper, we evaluate the use of a non-rigid registration method that uses optical flow equations to drive the displacement of a grid of control points. With conventional optical flow techniques it is assumed that changes in image intensity are solely due to motion, making it unsuitable for use with contrast-enhanced studies. The registration algorithm evaluated in this paper overcomes this problem by including an additional term to account for changes in image intensity. Studies simulating physiologically plausible deformations of the breast together with realistic changes in contrast-enhancement derived from patient studies demonstrate that the algorithm is capable of registering images to sub-voxel accuracy within minutes. This technique has now been successfully incorporated into a breast cancer screening protocol allowing registered images to be provided routinely to the radiologist immediately after the scanning session.

Abstract. In this paper we propose a method for the nonrigid registration of contrast-enhanced dynamic sequences of magnetic resonance(MR) images. The algorithm has been developed with accuracy in mind, but also has a clinically viable execution time (i.e. a few minutes) as a goal. The algorithm is driven by multiresolution optical flow with the brightness consistency assumption relaxed, subject to a regularized best-fit within a family of transforms. The particular family of transforms we have employed uses a grid of control points and trilinear interpolation. We present validation results from a study simulating non-rigid deformation by a biomechanical model of the breast, with simulated uptake of a contrast agent. We further present results from applying the algorithm as part of a routine breast cancer screening protocol.