Oudom Somphone

3D Strain Assessment in Ultrasound (Straus): A Synthetic Comparison of Five Tracking Methodologies

This paper evaluates five 3D ultrasound tracking algorithms regarding their ability to quantify abnormal deformation in timing or amplitude. A synthetic database of B-mode image sequences modeling healthy, ischemic and dyssynchrony cases was generated for that purpose. This database is made publicly available to the community. It combines recent advances in electromechanical and ultrasound modeling. For modeling heart mechanics, the Bestel-Clement-Sorine electromechanical model was applied to a realistic geometry. For ultrasound modeling, we applied a fast simulation technique to produce realistic images on a set of scatterers moving according to the electromechanical simulation result. Tracking and strain accuracies were computed and compared for all evaluated algorithms. For tracking, all methods were estimating myocardial displacements with an error below 1 mm on the ischemic sequences. The introduction of a dilated geometry was found to have a significant impact on accuracy. Regarding strain, all methods were able to recover timing differences between segments, as well as low strain values. On all cases, radial strain was found to have a low accuracy in comparison to longitudinal and circumferential components.

Real-Time 3d image segmentation by user-constrained template deformation

We describe an algorithm for 3D interactive image segmentation by non-rigid implicit template deformation, with two main original features. First, our formulation incorporates user input as inside/outside labeled points to drive the deformation and improve both robustness and accuracy. This yields inequality constraints, solved using an Augmented Lagrangian approach. Secondly, a fast implementation of non-rigid template-to-image registration enables interactions with a real-time visual feedback. We validated this generic technique on 21 Contrast-Enhanced Ultrasound images of kidneys and obtained accurate segmentation results (Dice > 0.93) in less than 3 clicks in average.

Non-Rigid Image Registration using a Hierarchical Partition of Unity Finite Element Method

We use a hierarchical partition of unity finite element method (H-PUFEM) to represent and analyse the non-rigid deformation fields involved in multidimensional image registration. We make use of the Ritz-Galerkin direct variational method to solve non-rigid image registration problems with various deformation constraints. In this method, we directly seek a set of parameters that minimizes the objective function. We thereby avoid the loss of information that may occur when an Euler-Lagrange formulation is used. Experiments are conducted to demonstrate the advantages of our approach when registering synthetic images having little of or no localizing features. As a special case, conformal mapping problems can be accurately solved in this manner. We also illustrate our approach with an application to cardiac magnetic resonance temporal sequences.

Detailed Evaluation of Five 3D Speckle Tracking Algorithms Using Synthetic Echocardiographic Recordings

A plethora of techniques for cardiac deformation imaging with 3D ultrasound, typically referred to as 3D speckle tracking techniques, are available from academia and industry. Although the benefits of single methods over alternative ones have been reported in separate publications, the intrinsic differences in the data and definitions used makes it hard to compare the relative performance of different solutions. To address this issue, we have recently proposed a framework to simulate realistic 3D echocardiographic recordings and used it to generate a common set of ground-truth data for 3D speckle tracking algorithms, which was made available online. The aim of this study was therefore to use the newly developed database to contrast non-commercial speckle tracking solutions from research groups with leading expertise in the field. The five techniques involved cover the most representative families of existing approaches, namely block-matching, radio-frequency tracking, optical flow and elastic image registration. The techniques were contrasted in terms of tracking and strain accuracy. The feasibility of the obtained strain measurements to diagnose pathology was also tested for ischemia and dyssynchrony.

Prior-Based Piecewise-Smooth Segmentation by Template Competitive Deformation Using Partitions of Unity

We propose a new algorithm for two-phase, piecewise-smooth segmentation with shape prior. The image is segmented by a binary template that is deformed by a regular geometric transformation. The choice of the template together with the constraint on the transformation introduce the shape prior. The deformation is guided by the maximization of the likelihood of foreground and background intensity models, so that we can refer to this approach as Competitive Deformation. In each region, the intensity is modelled as a smooth approximation of the original image. We represent the transformation using a Partition of Unity Finite Element Method, which consists in representing each component with polynomial approximations within local patches. A conformity constraint between the patches provides a way to control the globality of the deformation. We show several results on synthetic images, as well as on medical data from different modalities.

Computational and physical phantom setups for the second cardiac motion analysis challenge (cMAC2)

This paper describes the data setup of the second cardiac Motion Analysis Challenge (cMac2). The purpose of this challenge is to initiate a public data repository for the benchmark of motion and strain quantification algorithms on 3D ultrasound images. The data currently includes synthetic images that combine ultrasound and biomechanical simulators. We also collected sonomicrometry curves and ultrasound images acquired on a Polyvinyl alcohol phantom.

Motion estimation in 3d echocardiography using smooth field registration

This paper describes an algorithm for motion and deformation quantification of 3D cardiac ultrasound sequences. The algorithm is based on the assumption that the deformation field is smooth inside the myocardium. Thus, we assume that the displacement field can be represented as the convolution of an unknown field with a Gaussian kernel. We apply our algorithm to datasets with reliable ground truth: a set of synthetic sequences with known trajectories and a set of sequences of a mechanical phantom implanted with microsonometry crystals.

Robust image registration based on a Partition of Unity Finite Element Method

In this paper, we present a robust, hierarchical partition of unity finite element method (PUFEM) to compute the transformation between two images, which is represented by a non-rigid, locally polynomial displacement field. The partition of unity property offers an efficient optimization scheme by breaking down the global minimization of the mismatch energy into independent, local minimizations. Moreover, the regularization introduced by our approach enables us to control the range of the smoothness. Our method was applied to cardiac ultrasound image sequences to propagate the segmentation of anatomical structures of interest.

Improvements of Myocardial Deformation Assessment by Three-Dimensional Speckle-Tracking versus Two-Dimensional Speckle-Tracking Revealed by Cardiac Magnetic Resonance Tagging

Background: In prior work, the authors demonstrated that two‐dimensional speckle‐tracking (2DST) correlated well but systematically overestimated global longitudinal strain (LS) and circumferential strain (CS) compared with two‐dimensional cardiac magnetic resonance tagging (2DTagg) and had poor agreement on a segmental basis. Because three‐dimensional speckle‐tracking (3DST) has recently emerged as a new, more comprehensive evaluation of myocardial deformation, this study was undertaken to evaluate whether it would compare more favorably with 2DTagg than 2DST. Methods: In a prospective two‐center trial, 119 subjects (29 healthy volunteers, 63 patients with left ventricular dysfunction, and 27 patients with left ventricular hypertrophy) underwent 2DST, 3DST, and 2DTagg. Global, regional (basal, mid, and apical), and segmental (18 and 16 segments per patient) LS and CS by 2DST and 3DST were compared with 2DTagg using intraclass correlation coefficients (ICCs) and Bland‐Altman analysis. Test‐retest reproducibility of 3DST and 2DST was compared in 48 other patients. Results: Both global LS and CS by 3DST agreed better with 2DTagg (ICC = 0.89 and ICC = 0.83, P < .001 for both; bias = 0.5 ± 2.3% and 0.2 ± 3%) than 2DST (ICC = 0.65 and ICC = 0.55, P < .001 for both; bias = −5.5 ± 2.5% and −7 ± 5.3%). Unlike 2DST, 3DST did not overestimate deformation at the regional and particularly the apical levels and at the segmental level had lower bias (LS, 0.8 ± 2.8% vs −5.3 ± 2.4%; CS, −0.01 ± 2.8% vs −7 ± 2.8%, respectively) but similar agreement with 2DST (LS: ICC = 0.58 ± 0.16 vs 0.56 ± 0.12; CS: ICC = 0.58 ± 0.12 vs 0.51 ± 0.1) with 2DTagg. Finally, 3DST had similar global LS, but better global CS test‐retest variability than 2DST. Conclusions: Using 2DTagg as reference, 3DST had better agreement and less bias for global and regional LS and CS. At the segmental level, 3DST demonstrated comparable agreement but lower bias versus 2DTagg compared with 2DST. Also, test‐retest variability for global CS by 3DST was better than by 2DST. This suggests that 3DST is superior to 2DST for analysis of global and regional myocardial deformation, but further refinement is needed for both 3DST and 2DST at the segmental level. HIGHLIGHTS3DST GLS and GCS agreed better with 2DTagg than 2DST.Unlike 2DST, 3DST did not overestimate GCS vs 2DTagg.Segmental strains by both 3DSTand 2DST agreed suboptimally with 2DTagg.3DST and 2DST test‐retest reproducibility were similar for GLS. 3DST had better GCS test‐retest reproducibility than 2DST.

Ultrafast cardiac 2D vector flow imaging

Left intraventricular blood vortices could provide important information on cardiovascular health. However they are not explicitly measured in current-day commercial systems. Additionally, the slow frame rates (typically <30Hz) of 2D cardiac Doppler imaging do not enable adequate sampling of the intraventricular blood dynamics. Finally, current imaging modes do not allow simultaneous estimation of cardiac and blood motion. The objective of this study was to combine ultrafast imaging and vector flow imaging to achieve fully sampled, 2D velocity vector imaging transthoracically in the left ventricle together with synchronous myocardial motion imaging. A new imaging mode based on those principles may give new insights onto the coupling between mechanical and hemodynamic cardiac function.