Sparsity and biomechanics inspired integration of shape and speckle tracking for cardiac deformation analysis

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Abstract

Cardiac motion analysis, particularly of the left ventricle (LV), can provide valuable information regarding the functional state of the heart. We propose a strategy of combining shape tracking and speckle tracking based displacements to calculate the dense deformation field of the myocardium. We introduce the use and effects of l1 regularization, which induces sparsity, in our integration method. We also introduce regularization to make the dense fields more adhering to cardiac biomechanics. Finally, we motivate the necessity of temporal coherence in the dense fields and demonstrate a way of doing so. We test our method on ultrasound (US) images acquired from six open-chested canine hearts. Baseline and post-occlusion strain results are presented for an animal, where we were able to detect significant change in the ischemic region. Six sets of strain results were also compared to strains obtained from tagged magnetic resonance (MR) data. Median correlation (with MR-tagging) coefficients of 0.73 and 0.82 were obtained for radial and circumferential strains respectively.

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Parajuli, N., Compas, C. B., Lin, B. A., Sampath, S., O’Donnell, M., Sinusas, A. J., & Duncan, J. S. (2015). Sparsity and biomechanics inspired integration of shape and speckle tracking for cardiac deformation analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9126, pp. 57–64). Springer Verlag. https://doi.org/10.1007/978-3-319-20309-6_7

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