Right ventricle extraction by low level and model-based algorithm

In this paper we present an algorithm as the combination of a low level morphological operation and model based Global Circular Shortest Path scheme to explore the segmentation of the Right Ventricle. Traditional morphological operations were employed to obtain the region of interest, and adjust it to generate a mask. The image cropped by the mask is then partitioned into a few overlapping regions. Global Circular Shortest Path algorithm is then applied to extract the contour from each partition. The final step is to re-assemble the partitions to create the whole contour. The technique is deemed quite reliable and robust, as this is illustrated by a very good agreement between the extracted contour and the expert manual drawing output.

Analysis of cardiac ventricular wall motion based on a three-dimensional electromechanical biventricular model

This paper describes a biventricular model, which couples the electrical and mechanical properties of the heart, and computer simulations of ventricular wall motion and deformation by means of a biventricular model. In the constructed electromechanical model, the mechanical analysis was based on composite material theory and the finite-element method; the propagation of electrical excitation was simulated using an electrical heart model, and the resulting active forces were used to calculate ventricular wall motion. Regional deformation and Lagrangian strain tensors were calculated during the systole phase. Displacements, minimum principal strains and torsion angle were used to describe the motion of the two ventricles. The simulations showed that during the period of systole, (1) the right ventricular free wall moves towards the septum, and at the same time, the base and middle of the free wall move towards the apex, which reduces the volume of the right ventricle; the minimum principle strain (E3) is largest at the apex, then at the middle of the free wall and its direction is in the approximate direction of the epicardial muscle fibres; (2) the base and middle of the left ventricular free wall move towards the apex and the apex remains almost static; the torsion angle is largest at the apex; the minimum principle strain E3 is largest at the apex and its direction on the surface of the middle wall of the left ventricle is roughly in the fibre orientation. These results are in good accordance with results obtained from MR tagging images reported in the literature. This study suggests that such an electromechanical biventricular model has the potential to be used to assess the mechanical function of the two ventricles, and also could improve the accuracy ECG simulation when it is used in heart torso model-based body surface potential simulation studies.

Motion analysis of right ventricular wall based on an electromechanical biventricular model

Based on our previously developed electrical heart model, an electromechanical biventricular model, which couples the electrical property and mechanical property of the heart, was constructed and the right ventricular wall motion and deformation was simulated using this model. The model was developed on the basis of composite material theory and finite element method. The excitation propagation was simulated by electrical heart model, and the resultant active forces were used to study the ventricular wall motion during systole. The simulation results show that: (1) The right ventricular free wall moves towards the septum, and at the same time, the base and middle of free wall move towards the apex, which reduce the volume of right ventricle; (2) The minimum principle strain (E3) is largest at the apex, then at the middle of free wall, and its direction is in the approximate direction of epicardial muscle fibers. These results are in good accordance with solutions obtained from MR tagging images. It suggests that such electromechanical biventricular model can be used to assess the mechanical function of two ventricles.

Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images

Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Exercise ech predicts development of late post-operative left ventricular dysfunction and cardiac morbidity in asymptomatic severe mitral regurgitation

Objective: Mitral repair is increasingly performed in asymptomatic mitral regurgitation (MR). Previous work showed that pre-operative documentation of loss of contractile reserve (Cr) by exercise echo (ExE) may predict LV dysfunction early after repair. We sought the value of Cr in predicting late post-op LV dysfunction and clinical outcome. Methods: Pre-op ExE was performed in 41 pts with isolated MR without coronary disease undergoing repair. LV end-systolic and end-diastolic volumes were measured at rest and post-stress and EF was calculated using modified Simpson’s rule. Intact Cr was defined by >4% increment of stress compared with rest EF. During follow up (3±1 years), EF was serially assessed and occurrence of cardiac events was documented. Results: Cr was present in 19 pts (Cr+)(peak EF 76±7%) and absent in 22 pts (Cr-)(peak EF 56±11%, p