Generalized cystic resolution: a metric for assessing the fundamental limits on beamformer performance

Abstract-Constructing a double-curved row-columnaddressed (RCA) 2-D array or applying a diverging lens over the flat RCA 2-D array can extend the imaging field-of-view (FOV) to a curvilinear volume without increasing the aperture size, which is necessary for applications such as abdominal and cardiac imaging. Extended FOV and low channel count of double-curved RCA 2-D arrays make 3-D imaging possible with equipment in the price range of conventional 2-D imaging. This study proposes a delay-and-sum beamformation scheme specific to double-curved RCA 2-D arrays and validates its focusing ability based on simulations. A synthetic aperture imaging sequence with single element transmissions is designed for imaging down to 14 cm at a volume rate of 88 Hz. Using a diverging lens with f-number of -1 circumscribing the underlying RCA array, the imaging quality of a double-curved λ/2-pitch 3 MHz 62+62 RCA 2-D array is investigated as a function of depth within a curvilinear FOV of 60°×60°. The simulated double-curved 2-D array exhibits the same full-width-at-halfmaximum values for a point scatterer within its curvilinear FOV at a fixed radial distance compared with a flat 2-D array within its rectilinear FOV. The results of this study demonstrate that the proposed beamforming approach is accurate for achieving correct time-of-flight calculations, and hence avoids geometrical distortions.

Section: B Imaging Quality Assessment Measuresmentioning

confidence: 99%

Curvilinear 3-D Imaging Using Row-Column-Addressed 2-D Arrays With a Diverging Lens: Feasibility Study

Bouzari

Engholm

Beers

et al. 2017

“…Some example mechanisms include diffraction limited beam width and reverberation [1], multiple scattering (sometimes considered distinct from reverberation) [2], and sound speed inhomogeneities [3]. Generally, in recent literature, beamforming based image degradation—including diffraction limitations and sound speed inhomogeneity—is widely considered the dominant source of in vivo image corruption [4]–[7]. Many beamforming algorithms have been explored to improve image quality by reducing the clutter caused by scattering located away from the beam-axis (off-axis).…”

Section: Introductionmentioning

confidence: 99%

Ultrasonic multipath and beamforming clutter reduction: a chirp model approach

Byram

Jakovljevic

2014

In vivo ultrasonic imaging with transducer arrays suffers from image degradation due to beamforming limitations, which includes diffraction limited beamforming as well as beamforming degradation due to tissue inhomogeneity. Additionally, based on recent studies, multipath scattering also causes significant image degradation. To reduce degradation from both sources, we propose a model-based, signal decomposition scheme. The proposed algorithm identifies spatial frequency signatures to decompose received wavefronts into their most significant scattering sources. Scattering sources originating from a region of interest are used to reconstruct decluttered wavefronts, which are beamformed into decluttered radio frequency (RF) scan lines or A-lines. To test the algorithm, ultrasound system channel data were acquired during liver scans from 8 patients. Multiple data sets were acquired from each patient, with 55 total data sets, 43 of which had identifiable hypoechoic regions on normal B-mode images. The data sets with identifiable hypoechoic regions were analyzed. The results show the decluttered B-mode images have an average improvement in contrast over normal images of 7.3±4.6 dB. The CNR changed little on average between normal and decluttered B-mode, −0.4±5.9 dB. The in vivo speckle SNR decreased; the change was −0.65±0.28. Phantom speckle SNR also decreased but only by −0.40±0.03.

“…To simplify calculations and simulations, our error analysis has focused on the main lobe level, instead of the Msr degradation or similar metrics such as generalized cystic resolution [30]. although energy conservation is never completely fulfilled in ultrasound imaging where the far field assumption and continuous wave operation do not strictly hold, the magnitude of the side lobe increase has the expected relationship to the main lobe coherence loss.…”

Section: Discussionmentioning

confidence: 99%

Error analysis of subaperture processing in 1-D ultrasound arrays

Zhao

Bjåstad

Kristoffersen

2015

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.