Showing papers by "Gemma Piella published in 2011"

Temporal diffeomorphic free form deformation (TDFFD) applied to motion and deformation quantification of tagged MRI sequences

Abstract: This paper presents strain quantification results obtained from the Tagged Magnetic Resonance Imaging (TMRI) sequences acquired for the 1st cardiac Motion Analysis Challenge (cMAC). We applied the Temporal Diffeomorphic Free Form Deformation (TDFFD) algorithm to the phantom and the 15 healthy volunteers of the cMAC database. The TDFFD was modified in two ways. First, we modified the similarity metric to incorporate frame to frame intensity differences. Second, on volunteer sequences, we performed the tracking backward in time since the first frames did not show the contrast between blood and myocardium, making these frames poor choices of reference. On the phantom, we propagated a grid adjusted to tag lines to all frames for visually assessing the influence of the different algorithmic parameters. The weight between the two metric terms appeared to be a critical parameter for making a compromise between good tag tracking while preventing drifts and avoiding tag jumps. For each volunteer, a volumetric mesh was defined in the Steady-State Free Precession (SSFP) image, at the closest cardiac time from the last frame of the tagging sequence. Uniform strain patterns were observed over all myocardial segments, as physiologically expected.

Multiview diffeomorphic registration for motion and strain estimation from 3D ultrasound sequences

Abstract: This paper presents a new registration framework for estimating myocardial motion and strain from multiple views of 3D ultrasound sequences. The originality of our approach resides in the estimation of the transformation directly from the multiple views rather than from a single view or a reconstructed compounded sequence. This allows us to exploit all spatio-temporal information available in the input views avoiding occlusions and image fusion errors that could lead to some inconsistencies in the motion quantification result. In addition, by using the original input images, speckle information (which is an important feature for motion estimation and could be blurred out in the fusion process) should remain consistent between temporal image frames. We propose a multiview diffeomorphic registration strategy that enforces smoothness and consistency in the spatio-temporal domain by modeling a continuous 3D+t velocity field as a sum of B-spline kernels. This 3D+t continuous representation allows us to robustly cope with variations in heart rate resulting in different number of images acquired per cardiac cycle for different views. The similarity measure is obtained by extension of a pairwise mean square error metric where a weighting scheme balances the contribution of the different views. We have carried out experiments on synthetic 3D ultrasound images with known ground truth and on in-vivo multiview 3D data sets of two volunteers. It is shown that the inclusion of several views improves the consistency of the strain curves and reduces the number of segments where a non-physiological strain pattern is observed.

Characterizing pathological deviations from normality using constrained manifold-learning

Abstract: We propose a technique to represent a pathological pattern as a deviation from normality along a manifold structure. Each subject is represented by a map of local motion abnormalities, obtained from a statistical atlas of motion built from a healthy population. The algorithm learns a manifold from a set of patients with varying degrees of the same pathology. The approach extends recent manifold-learning techniques by constraining the manifold to pass by a physiologically meaningful origin representing a normal motion pattern. Individuals are compared to the manifold population through a distance that combines a mapping to the manifold and the path along the manifold to reach its origin. The method is applied in the context of cardiac resynchronization therapy (CRT), focusing on a specific motion pattern of intra-ventricular dyssynchrony called septal flash (SF). We estimate the manifold from 50 CRT candidates with SF and test it on 38 CRT candidates and 21 healthy volunteers. Experiments highlight the need of nonlinear techniques to learn the studied data, and the relevance of the computed distance for comparing individuals to a specific pathological pattern.

Cardiac Deformation from Electro-Anatomical Mapping Data: Application to Scar Characterization

Abstract: We propose in this paper a new way of calculating an endocardial end-systolic deformation parameter from electro-anatomical data acquired intra-operatively during electrophysiology interventions. The estimated parameter is then used to study deformation in regions with different viability properties: scar, border zone and normal myocardial tissue. These regions are defined based on electrophysiological data acquired with a contact mapping system, specifically with the bipolar voltage maps and a set of routinely used thresholds. The obtained results when applying our methodology on a set of 8 cases show statistically significant differences between the average deformation values of the scar, border zone and normal myocardial tissue areas, thus demonstrating the feasibility of detecting changes in deformation between normal and non-healthy tissue from electro-anatomical maps. Nevertheless, although low deformation regions more often correspond to non-healthy tissue, deformation is not an accurate indicator of viability abnormalities.