Strain Curve Classification Using Supervised Machine Learning Algorithm with Physiologic Constraints.

Speckle tracking echocardiography (STE) enables quantification of myocardial deformation by a generation of spatiotemporal strain curves or time-strain curves (TSCs). Currently, only assessment of peak global longitudinal strain is employed in clinical practice because of the uncertainty in the accuracy of STE. We describe a supervised machine learning, physiologically constrained, fully automatic algorithm, trained with labeled data, for classification of TSCs into physiologic or artifactual classes.

High-Resolution Fast Ultrasound Imaging With Adaptive-Lag Filtered Delay-Multiply-and-Sum Beamforming and Multiline Acquisition.

Multiline acquisition (MLA) is a well-established method for a high-frame-rate cardiac ultrasound imaging, which is commonly used in conjunction with delay-and-sum (DAS) beamforming. The block-like artifacts that occur secondary to the use of MLA can be reduced using interpolation of the data acquired from adjacent transmitted beams-a method called synthetic transmit beamforming (STB). A recently proposed filtered delay-multiply-and-sum (F-DMAS) is a novel beamforming method, based on modified autocorrelation of the aperture data, which provides superior contrast resolution compared to the DAS beamforming.

Multi Line Transmit Beamforming Combined With Adaptive Apodization.

Increased frame rate is of high importance to cardiac diagnostic imaging as it enables examination of fast events during the cardiac cycle and improved quantitative analysis, such as speckle tracking. Multi-line transmission (MLT) is one of the methods proposed for this purpose. In contrast to the single-line transmission (SLT), where one focused beam is sent in each direction, MLT beams are simultaneously transmitted and focused in several (2,4,6.

Multiline Transmit Beamforming Combined With Adaptive Apodization.

Increased frame rate is of high importance to cardiac diagnostic imaging as it enables examination of fast events during the cardiac cycle and improved quantitative analysis, such as speckle tracking. Multiline transmission (MLT) is one of the methods proposed for this purpose. In contrast to the single-line transmission (SLT), where one focused beam is sent in each direction, MLT beams are simultaneously transmitted and focused in several ( ) directions improving the frame rate accordingly.

Automatic apical view classification of echocardiograms using a discriminative learning dictionary.

As part of striving towards fully automatic cardiac functional assessment of echocardiograms, automatic classification of their standard views is essential as a pre-processing stage. The similarity among three of the routinely acquired longitudinal scans: apical two-chamber (A2C), apical four-chamber (A4C) and apical long-axis (ALX), and the noise commonly inherent to these scans - make the classification a challenge. Here we introduce a multi-stage classification algorithm that employs spatio-temporal feature extraction (Cuboid Detector) and supervised dictionary learning (LC-KSVD) approaches to uniquely enhance the automatic recognition and classification accuracy of echocardiograms.

Evaluation of a 3D technique for quantifying neovascularization within plaques imaged by contrast enhanced ultrasound.

Intra-plaque neovascularization and inflammation are considered as important indicators of plaque vulnerability, which when ruptured, may cause stroke or acute myocardial infarction. The purpose of this research was to validate and evaluate a semi-automatic method, which allows quantification of carotid plaque neovascularization using contrast-enhanced ultrasound cines, thus enabling assessment of plaque vulnerability. The method detects contrast clusters in the images, and tracks them, to generate over time a path that portrays the neovasculature.