This work proposes a novel analysis of the left ventricular chamber dynamics from ultrasound 2D videos, in four steps: first the left ventricular chamber is segmented and second a multi-orientation and multi-scale filtering is performed. A third step is the chamber partition in similar number of super-pixels or homogeneous regions. The final step extracts features from the velocity-acceleration phase plane constructed by tracking these regions along the cardiac cycle and estimating their velocity and acceleration. Finally, each case is characterized by dividing the phase plane into three disjoint areas along the radial direction and estimating the density of points per region. This approach was evaluated in actual videos of four subjects, two control and two patients. Results show density means for unhealthy and control as follows: 0.63 and 0.45 for the low motion region, 0.26 and 0.4 for the mid motion region, and 0.1 and 0.1 for the high motion region.
Speckle noise filtering has been investigated since at least fifty years, this multiplicative and granular interference may be found in any image, i.e, Synthetic Aperture Radar (SAR), optical coherence tomography, and of course, medical ultrasound imaging. Speckle noise is produced by structural characteristics of materials, in case of the ultrasound imaging case, by small structural irregularities. This work proposes a novel speckle noise filtering strategy using a bank of morphological multi-scale filters that captures anisotropic information and additionally preserves cardiac structures. This method is compared against commonly used filters, namely: Anisotropic Diffusion Filter (ADMSS), Non-Local Means Filter (NLMF) and Detail Preserving Anisotropic Diffusion Filter (DPAD).
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