A Very Large Cardiac Channel Data Database (VLCD) Used to Evaluate Global Image Coherence (GIC) as an In Vivo Image Quality Metric.

Ultrasound image quality is of utmost importance for a clinician to reach a correct diagnosis. Conventionally, image quality is evaluated using metrics to determine the contrast and resolution. These metrics require localization of specific regions and targets in the image such as a region of interest (ROI), a background region, and/or a point scatterer. Such objects can all be difficult to identify in in-vivo images, especially for automatic evaluation of image quality in large amounts of data. Using a matrix array probe, we have recorded a Very Large cardiac Channel data Database (VLCD) to evaluate coherence as an in vivo image quality metric. The VLCD consists of 33280 individual image frames from 538 recordings of 106 patients. We also introduce a global image coherence (GIC), an in vivo image quality metric that does not require any identified ROI since it is defined as an average coherence value calculated from all the data pixels used to form the image, below a preselected range. The GIC is shown to be a quantitative metric for in vivo image quality when applied to the VLCD. We demonstrate, on a subset of the dataset, that the GIC correlates well with the conventional metrics contrast ratio (CR) and the generalized contrast-to-noise ratio (gCNR) with R = 0.74 ( ) and R = 0.62 ( ), respectively. There exist multiple methods to estimate the coherence of the received signal across the ultrasound array. We further show that all coherence measures investigated in this study are highly correlated ( 0.9 and ) when applied to the VLCD. Thus, even though there are differences in the implementation of coherence measures, all quantify the similarity of the signal across the array and can be averaged into a GIC to evaluate image quality automatically and quantitatively.

Clutter Filter Wave Imaging.

The elastic properties of human tissue can be evaluated through the study of mechanical wave propagation captured using high frame rate ultrasound imaging. Methods such as block-matching or phase-based motion estimation have been used to estimate the displacement induced by the mechanical waves. In this paper, a new method for detecting mechanical wave propagation without motion estimation is presented, where the motion of interest is accentuated by an appropriate clutter filter. Thus, the mechanical wave propagation will directly appear as bands of the attenuated signal moving in the B-mode sequence and corresponding anatomical M-mode images. While only the locality of tissue velocity induced by the mechanical wave is detected, it is shown that the method is more sensitive to subtle tissue displacements when compared to motion estimation techniques. The technique was evaluated for the propagation of the pulse wave in a carotid artery, mechanical waves on the left ventricle, and shear waves induced by radiation force on a tissue-mimicking phantom. The results were compared to tissue Doppler imaging (TDI) and demonstrated that clutter filter wave imaging (CFWI) was able to detect the mechanical wave propagating in tissue with a relative temporal and spatial resolution 30% higher and a relative consistency 40% higher than TDI. The results showed that CFWI was able to detect mechanical waves with a relative frequency content 40% higher than TDI in a shear wave imaging experiment.

Maximum Velocity Estimation in Coronary Arteries Using 3-D Tracking Doppler.

Several challenges currently prevent the use of Doppler echocardiography to assess blood flow in the coronary arteries. Due to the anatomy of the coronary tree, out-of-plane flow and high beam-to-flow angles easily occur. Transit-time broadening in regions with high velocities leads to overestimation of the maximum velocity envelope, which is a standard clinical parameter for flow quantification. In this paper, a commercial ultrasound system was locally modified to perform trans-thoracic, 3-D high frame-rate imaging of the coronary arteries. The imaging sequence was then combined with 3-D tracking Doppler for retrospective estimation of maximum velocities. Results from simulations showed that 3-D tracking Doppler delivers sonograms with better velocity resolution and spectral SNR compared to conventional pulsed wave (PW) Doppler. Results were confirmed using in vitro recordings. Further simulations based on realistic coronary flow data showed that 3-D tracking Doppler can provide improved performance compared to PW Doppler, suggesting a potential benefit to patients. In vivo feasibility of the method was also shown in a healthy volunteer.

Error analysis of subaperture processing in 1-D ultrasound arrays.

To simplify the medical ultrasound system and reduce the cost, several techniques have been proposed to reduce the interconnections between the ultrasound probe and the back-end console. Among them, subaperture processing (SAP) is the most straightforward approach and is widely used in commercial products. This paper reviews the most important error sources of SAP, such as static focusing, delay quantization, linear delay profile, and coarse apodization, and the impacts introduced by these errors are shown. We propose to use main lobe coherence loss as a simple classification of the quality of the beam profile for a given design. This figure-ofmerit (FoM) is evaluated by simulations with a 1-D ultrasound subaperture array setup. The analytical expressions and the coherence loss can work as a quick guideline in subaperture design by equalizing the merit degradations from different error sources, as well as minimizing the average or maximum loss over ranges. For the evaluated 1-D array example, a good balance between errors and cost was achieved using a subaperture size of 5 elements, focus at 40 mm range, and a delay quantization step corresponding to a phase of π/4.