Spline-Based Cardiac Motion Tracking Using Velocity-Encoded Magnetic Resonance Imaging

Abstract

This paper deals with the problem of tracking cardiac motion and deformation using velocity-encoded magnetic resonance imaging. We expand upon an earlier described method and fit a spatiotemporal motion model to measured velocity data. We investigate several different spatial elements both qualitatively and quantitatively using phantom measurements and data from human subjects. In addition, we also use optical flow estimation by the Horn-Schunk method as complementary data in regions where the velocity measurements are noisy. Our results show that it is possible to obtain good motion tracking accuracy in phantoms with relatively few spatial elements, if the type of element is properly chosen. The use of optical flow can correct some measurement artifacts but may give an underestimation of the magnitude of the deformation. In human subjects the different spatial elements perform quantitatively in a similar way but qualitative differences exists, as shown by a semiquantitative visual scoring of the different methods.

Novel insight into the detailed myocardial motion and deformation of the rodent heart using high-resolution phase contrast cardiovascular magnetic resonance

“…1) is rather simple compared to more complex approaches, such as spline-based deformation analysis [41]. However, the presented results suggest that our approach is appropriate, yielding accurate and reproducible results.…”

A semiautomatic method for rapid segmentation of velocity‐encoded myocardial magnetic resonance imaging data

“…Semiautomatic LV contour tracking has been used previously in displacement‐encoded images . Moreover, the concept of using velocity‐guided segmentation of the myocardium is not new . However, compared with earlier velocity‐based approaches, our method is inherently simple to implement as it requires no a priori knowledge of object shape for constraining the segmentation.…”

“…Different approaches have been proposed to improve and/or simplify left ventricular (LV) segmentation in TPM data sets, typically related to either pixel tracking or contour propagation. Pixel tracking has been applied successfully for deformation and strain analysis from TPM data , but has not been used to map the myocardial velocities directly. Contour propagation based on tracking the blood‐myocardium border using active contour models have been suggested as a tool to analyze velocities directly , but depends on a priori knowledge of object shape for constraining the segmentation and is sensitive to velocity aliasing and blood turbulence .…”

Effects of gadolinium contrast agent on aortic blood flow and myocardial strain measurements by phase-contrast cardiovascular magnetic resonance

“…Delineation of the left ventricular myocardium was performed manually in the first time-frame of each set of magnitude images acquired before contrast agent administration. The previously described automated and validated technique with a fitted spatiotemporal motion model was used for propagation throughout all time-frames[1,12]. The mask was then transferred to the PC images acquired pre and post contrast agent administration for measurement of myocardial displacement.…”

“…Aspects of regional function such as motion and myocardial displacement can be measured using phase-contrast cardiovascular magnetic resonance (PC-CMR). Myocardial strain can then be calculated from myocardial displacement[1]. …”