Evaluation of Performance Tradeoffs When Using Mechanically Swept 1-D Linear Arrays for 3-D DCE-US.

Dynamic contrast-enhanced ultrasound imaging (DCE-US) may be used to characterize tumor vascular perfusion using metrics derived from time-amplitude curves (TACs). The 3-D DCE-US enables generation of 3-D parametric maps of TAC metrics that may inform on how perfusion varies across the entire tumor. The aim of this work was to understand the effect of low temporal sampling (i.e., < 1 Hz) typical of 3-D imaging using a swept 1-D array transducer on the evaluation of TAC metrics and the effect of transducer motion in combination with flow on 3-D parametric maps generated using both plane wave imaging (PWI) (seven angles) and focused imaging (FI). Correlation maps were introduced to evaluate the spatial blurring of TAC metrics. A research ultrasound scanner and a pulse-inversion algorithm were used to obtain DCE-US. The 2-D (frame rate 10 Hz) and 3-D (volume rate 0.4 Hz) images were acquired of a simple wall-less vessel phantom (flow phantom) and a cartridge phantom. Volumetric imaging provided similar TACs to that of the higher 2-D sampling rate. Varying sweep speed and acceleration/deceleration had little influence on the 3-D TAC compared to 2-D for both FI and PWI. Sweeping motion and limited temporal sampling (0.4 Hz) did not change the spatial correlation of TAC metrics measured using FI, whereas a small increase in correlation across the cartridge phantom was observed for PWI. This was attributed to grating lobe artifacts, broad beam spatial blurring, and incoherent compounding caused by motion. Increased correlation will reduce the spatial resolution with which inhomogeneity of vascular perfusion can be mapped supporting the choice of FI for DCE-US.

Plane wave versus focused transmissions for contrast enhanced ultrasound imaging: the role of parameter settings and the effects of flow rate on contrast measurements.

Contrast enhanced ultrasound (CEUS) and dynamic contrast enhanced ultrasound (DCE-US) can be used to provide information about the vasculature aiding diagnosis and monitoring of a number of pathologies including cancer. In the development of a CEUS imaging system, there are many choices to be made, such as whether to use plane wave (PW) or focused imaging (FI), and the values for parameters such as transmit frequency, F-number, mechanical index, and number of compounding angles (for PW imaging). CEUS image contrast may also be dependent on subject characteristics, e.g. flow speed and vessel orientation. We evaluated the effect of such choices on vessel contrast for PW and FI in vitro, using 2D ultrasound imaging. CEUS images were obtained using a VantageTM (Verasonics Inc.) and a pulse-inversion (PI) algorithm on a flow phantom. Contrast (C) and contrast reduction (CR) were calculated, where C was the initial ratio of signal in vessel to signal in background and CR was its reduction after 200 frames (acquired in 20 s). Two transducer orientations were used: parallel and perpendicular to the vessel direction. Similar C and CR was achievable for PW and FI by choosing optimal parameter values. PW imaging suffered from high frequency grating lobe artefacts, which may lead to degraded image quality and misinterpretation of data. Flow rate influenced the contrast based on: (1) false contrast increase due to the bubble motion between the PI positive and negative pulses (for both PW and FI), and (2) contrast reduction due to the incoherency caused by bubble motion between the compounding angles (for PW only). The effects were less pronounced for perpendicular transducer orientation compared to a parallel one. Although both effects are undesirable, it may be more straight forward to account for artefacts in FI as it only suffers from the former effect. In conclusion, if higher frame rate imaging is not required (a benefit of PW), FI appears to be a better choice of imaging mode for CEUS, providing greater image quality over PW for similar rates of contrast reduction.

Synthetic Aperture Ultrasound Fourier Beamformation Using Virtual Sources.

An efficient Fourier beamformation algorithm is presented for multistatic synthetic aperture ultrasound imaging using virtual sources. The concept is based on the frequency domain wavenumber algorithm from radar and sonar and is extended to a multielement transmit/receive configuration using virtual sources. Window functions are used to extract the azimuth processing bandwidths and weight the data to reduce side lobes in the final image. Field II simulated data and SARUS (Synthetic Aperture Real-time Ultrasound System) measured data are used to evaluate the results in terms of point spread function, resolution, contrast, signal-to-noise ratio, and processing time. Lateral resolutions of 0.53 and 0.66 mm are obtained for Fourier Beamformation Using Virtual Sources (FBV) and delay and sum (DAS) on point target simulated data. Corresponding axial resolutions are 0.21 mm for FBV and 0.20 mm for DAS. The results are also consistent over different depths evaluated using a simulated phantom containing several point targets at different depths. FBV shows a better lateral resolution at all depths, and the axial and cystic resolutions of -6, -12, and -20 dB are almost the same for FBV and DAS. To evaluate the cyst phantom metrics, three different criteria of power ratio, contrast ratio, and contrast-to-noise ratio have been used. Results show that the algorithms have a different performance in the cyst center and near the boundary. FBV has a better performance near the boundary; however, DAS is better in the more central area of the cyst. Measured data from phantoms are also used for evaluation. The results confirm applicability of FBV in ultrasound, and 20 times less processing time is attained in comparison with DAS. Evaluating the results over a wide variety of parameters and having almost the same results for simulated and measured data demonstrates the ability of FBV in preserving the quality of image as DAS, while providing a more efficient algorithm with 20 times less computations.

Computational Complexity Reduction of Synthetic-aperture Focus in Ultrasound Imaging Using Frequency-domain Reconstruction.

A new frequency-domain implementation of a synthetic aperture focusing technique is presented in the paper. The concept is based on synthetic aperture radar (SAR) and sonar that is a developed version of the convolution model in the frequency domain. Compared with conventional line-by-line imaging, synthetic aperture imaging has a better resolution and contrast at the cost of more computational load. To overcome this problem, point-by-point reconstruction methods have been replaced by block-processing algorithms in radar and sonar; however, these techniques are relatively unknown in medical imaging. In this paper, we extended one of these methods called wavenumber to medical ultrasound imaging using a simple model of synthetic aperture focus. The model, derived here for monostatic mode, can be generalized to multistatic as well. The method consists of 4 steps: a 2D fast Fourier transform of the data, frequency shift of the data to baseband, interpolation to convert polar coordinates to rectangular ones, and returning the data to the spatial-domain using a 2D inverse Fourier transform. We have also used chirp pulse excitation followed by matched filtering and spotlighting algorithm to compensate the effect of differences in parameters between radar and medical imaging. Computational complexities of the two methods, wavenumber and delay-and-sum (DAS), have been calculated. Field II simulated point data have been used to evaluate the results in terms of resolution and contrast. Evaluations with simulated data show that for typical phantoms, reconstruction by the wavenumber algorithm is almost 20 times faster than classical DAS while retaining the resolution.

Retinal vessel segmentation using a multi-scale medialness function.

Recently, automated segmentation of retinal vessels in optic fundus images has been an important focus of much research. In this paper, we propose a multi-scale method to segment retinal vessels based on a weighted two-dimensional (2D) medialness function. The results of the medialness function are first multiplied by the eigenvalues of the Hessian matrix. Next, centerlines of vessels are extracted using noise reduction and reconnection procedures. Finally, vessel radii are estimated and retinal vessels are segmented. The proposed method is evaluated and compared with several recent methods using images from the DRIVE and STARE databases.