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Dimitris Metaxas

Publications and source records attributed to Dimitris Metaxas.

2 recordsLinked to original sources

In vivo strain and stress estimation of the heart left and right ventricles from MRI images.

Mechanical properties of the myocardium have been investigated intensively in the last four decades. Many complex strain energy functions have been used to estimate the stress-strain relationship of myocardium because the heart muscle is an inhomogeneous, anisotropic, and nearly incompressible material, which undergoes large deformations. These functions can be effective for fitting in vitro experimental data from myocardial stretch testing. However, it is difficult to model in vivo myocardium using these strain energy functions. Moreover, such estimates have so far been carried out almost exclusively on the left ventricle, because of the relative thinness and complex geometry of the right ventricle. Previous work from our research group has successful estimated the motion and deformation of both the left and the right ventricles, using data from noninvasive tagged magnetic resonance imaging. In this paper, we present a novel statistical model to estimate the in vivo material properties and strain and stress distribution in both ventricles, using such data. Two normal hearts and two hearts with right-ventricular hypertrophy (RVH) were studied and noticeable differences were found between the strain and stress distributions for normal volunteers and RVH patients. Compared to the strain energy function approach, our model is more intuitively understandable.

Humans↗

Human motion planning based on recursive dynamics and optimal control techniques.

This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling the motion of articulated figures. A quasi-Newton nonlinear programming technique (super-linear convergence) is implemented to solve minimum torque-based human motion-planning problems. The explicit analytical gradients needed in the dynamics are derived using a matrix exponential formulation and Lie algebra. Cubic spline functions are used to make the search space for an optimal solution finite. Based on our formulations, our method is well conditioned and robust, in addition to being computationally efficient. To better illustrate the efficiency of our method, we present results of natural looking and physically correct human motions for a variety of human motion tasks involving open and closed loop kinematic chains.

Algorithms↗