Analysis of 3-D Myocardial Motion in Tagged MR Images Using Nonrigid Image Registration

Abstract

Tagged magnetic resonance imaging (MRI) is unique in its ability to noninvasively image the motion and deformation of the heart in vivo, but one of the fundamental reasons limiting its use in the clinical environment is the absence of automated tools to derive clinically useful information from tagged MR images. In this paper, we present a novel and fully automated technique based on nonrigid image registration using multilevel free-form deformations (MFFDs) for the analysis of myocardial motion using tagged MRI. The novel aspect of our technique is its integrated nature for tag localization and deformation field reconstruction using image registration and voxel based similarity measures. To extract the motion field within the myocardium during systole we register a sequence of images taken during systole to a set of reference images taken at end-diastole, maximizing the normalized mutual information between the images. We use both short-axis and long-axis images of the heart to estimate the full four-dimensional motion field within the myocardium. We also present validation results from data acquired from twelve volunteers.

Benchmarking framework for myocardial tracking and deformation algorithms: An open access database

“…Implementation: in IUCL's implementation, myocardial motion was estimated from the first frame to each subsequent frame using a series of free-form deformations (Rueckert et al, 1999) as described in Chandrashekara et al (2004b).…”

“…The transformation found at the previous frame was used as initial set of parameters in the optimization (Rueckert et al, 1999;Chandrashekara et al, 2004b).…”

Nonrigid Image Registration with Subdivision Lattices: Application to Cardiac MR Image Analysis

“…By registering the images taken during the cardiac cycle (the source images) to the target images we can determine the movement of points within the myocardium over time. Registration is being achieved by finding the displacements of the base vertices defining the subdivision lattice based transformation such that when the transformation is applied to the source images, the weighted sum of the mutual information of the images being registered is maximized ( [4]). …”

“…Among the main difficulties encountered is the need to estimate through-plane motion which is compounded by the effects of patient and respiratory motion. Recent work on image registration based techniques for tagged MR image analysis have yielded promising results for obtaining clinically meaningful information ( [4,13,15]). The advantage of using image registration is that no assumptions are required about the nature of the tag pattern in the images.…”

“…mutual information) can account for the variation in tag intensity over time seen in tagged MR images. The approach in [4] uses free-form deformations (FFDs) to model the cardiac deformation. However, these models require the control points to be spaced on a regular grid covering the entire heart.…”