Photoacoustic imaging (PAI) is an emerging medical imaging modality capable of providing high spatial resolution of Ultrasound (US) imaging and high contrast of optical imaging. Delay-and-Sum (DAS) is the most common beamforming algorithm in PAI. However, using DAS beamformer leads to low resolution images and considerable contribution of off-axis signals. A new paradigm namely delay-multiply-and-sum (DMAS), which was originally used as a reconstruction algorithm in confocal microwave imaging, was introduced to overcome the challenges in DAS. DMAS was used in PAI systems and it was shown that this algorithm results in resolution improvement and sidelobe degrading. However, DMAS is still sensitive to high levels of noise, and resolution improvement is not satisfying. Here, we propose a novel algorithm based on DAS algebra inside DMAS formula expansion, double stage DMAS (DS-DMAS), which improves the image resolution and levels of sidelobe, and is much less sensitive to high level of noise compared to DMAS. The performance of DS-DMAS algorithm is evaluated numerically and experimentally. The resulted images are evaluated qualitatively and quantitatively using established quality metrics including signal-to-noise ratio (SNR), full-width-half-maximum (FWHM) and contrast ratio (CR). It is shown that DS-DMAS outperforms DAS and DMAS at the expense of higher computational load. DS-DMAS reduces the lateral valley for about 15 dB and improves the SNR and FWHM better than 13% and 30%, respectively. Moreover, the levels of sidelobe are reduced for about 10 dB in comparison with those in DMAS.

Double-Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear-Array Photoacoustic Imaging

In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers.

https://www.spiedigitallibrary.org/journals/Journal-of-Biomedical-Optics/volume-23/issue-2/026002/Linear-array-photoacoustic-imaging-using-minimum-variance-based-delay-multiply/10.1117/1.JBO.23.2.026002.pdf

Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm.

Photoacoustic imaging (PAI) is a promising medical imaging modality providing the spatial resolution of ultrasound imaging and the contrast of optical imaging. For linear-array PAI, a beamformer can be used as the reconstruction algorithm. Delay-and-sum (DAS) is the most prevalent beamforming algorithm in PAI. However, using DAS beamformer leads to low-resolution images as well as high sidelobes due to nondesired contribution of off-axis signals. Coherence factor (CF) is a weighting method in which each pixel of the reconstructed image is weighted, based on the spatial spectrum of the aperture, to mainly improve the contrast. We demonstrate that the numerator of the formula of CF contains a DAS algebra and propose the use of a delay-multiply-and-sum beamformer instead of the available DAS on the numerator. The proposed weighting technique, modified CF (MCF), has been evaluated numerically and experimentally compared to CF. It was shown that MCF leads to lower sidelobes and better detectable targets. The quantitative results of the experiment (using wire targets) show that MCF leads to for about 45% and 40% improvement, in comparison with CF, in the terms of signal-to-noise ratio and full-width-half-maximum, respectively.

Enhanced linear-array photoacoustic beamforming using modified coherence factor.

The standard technique used by commercial medical ultrasound systems to form B-mode images is delay and sum (DAS) beamforming. However, DAS often results in limited image resolution and contrast that are governed by the center frequency and the aperture size of the ultrasound transducer. A large number of elements lead to improved resolution but at the same time increase the data size and the system cost due to the receive electronics required for each element. Therefore, reducing the number of receiving channels while producing high-quality images is of great importance. In this paper, we introduce a nonlinear beamformer called COnvolutional Beamforming Algorithm (COBA), which achieves significant improvement of lateral resolution and contrast. In addition, it can be implemented efficiently using the fast Fourier transform. Based on the COBA concept, we next present two sparse beamformers with closed-form expressions for the sensor locations, which result in the same beam pattern as DAS and COBA while using far fewer array elements. Optimization of the number of elements shows that they require a minimal number of elements that are on the order of the square root of the number used by DAS. The performance of the proposed methods is tested and validated using simulated data, phantom scans, and in vivo cardiac data. The results demonstrate that COBA outperforms DAS in terms of resolution and contrast and that the suggested beamformers offer a sizable element reduction while generating images with an equivalent or improved quality in comparison with DAS.

Sparse Convolutional Beamforming for Ultrasound Imaging

In ultrasound (US) imaging, delay and sum (DAS) is the most common beamformer, but it leads to low-quality images. Delay multiply and sum (DMAS) was introduced to address this problem. However, the reconstructed images using DMAS still suffer from the level of side lobes and low noise suppression. Here, a novel beamforming algorithm is introduced based on expansion of the DMAS formula. We found that there is a DAS algebra inside the expansion, and we proposed use of the DMAS instead of the DAS algebra. The introduced method, namely double-stage DMAS (DS-DMAS), is evaluated numerically and experimentally. The quantitative results indicate that DS-DMAS results in an approximately 25% lower level of side lobes compared with DMAS. Moreover, the introduced method leads to 23%, 22% and 43% improvement in signal-to-noise ratio, full width at half-maximum and contrast ratio, respectively, compared with the DMAS beamformer.

Double-Stage Delay Multiply and Sum Beamforming Algorithm Applied to Ultrasound Medical Imaging.

Ultrasound image quality is related to the receive beamformer’s ability Delay and sum (DAS), a conventional beamformer, is combined with the coherence factor (CF) technique to suppress side lobe levels The purpose of this study is to improve these beamformer’s abilities It has been shown that extension of the receive aperture can improve the receive beamformer’s ability in radar studies This paper shows that the focusing quality of CF and CF+DAS in medical ultrasound can be increased by extension of the receive aperture’s length in phased synthetic aperture (PSA) imaging The 3-dB width of the main lobe in the receive beam related to CF focusing decreased to 055 mm using the proposed PSA compared to the conventional phased array (PHA) imaging, whose FWHM is about 09 mm The clutter-to-total-energy ratio (CTR) represented by R20 dB showed an improvement of 50 and 33% for CF and CF+DAS beamformers, respectively, with PSA as compared to PHA In addition, simulation results validated the effectiveness of PSA versus PHA In applications where there are no important limitations on the SNR, PSA imaging is recommended as it increases the ability of the receive beamformer for better focusing

Improving beamforming performance by phased synthetic aperture imaging in medical ultrasound

Phased subarray imaging (PSA) was previously proposed to extend the receive aperture length. Using overlapped subarrays as transmitters in PSA leads to decrement of sidelobe levels of the overall beam compared to full phased array imaging (PHA). This paper proposes an adaptive compounding of subarray images in PSA to improve both the resolution and contrast compared with PHA. Adaptive apodization (ADAP) is defined proportional to the beamformed responses of subarrays such that the overall energy after compounding is minimized. The simulation and experimental results validate the performance of applying ADAP in PSA. The full width at half maximum (FWHM) at a depth of 30 mm in the proposed PSA is about 0.2 mm, compared to a FWHM of 0.6 mm with PHA imaging. Measuring the contrast ratio index shows that the ADAP method also improves the contrast in PSA imaging at least 25% compared to PHA imaging. Applying the proposed ADAP, besides conventional compounding in PSA imaging, leads to improvement of both the resolution and contrast compared to PHA imaging.

A novel adaptive apodization to improve the resolution of phased subarray imaging in medical ultrasound

Phased Synthetic Aperture imaging (PSA) improves the resolution and frame rate compared to the conventional Phased Array imaging. In the proposed PSA, two subarrays at left and right sides of the array are utilized to scan the medium sequentially. In this study simultaneous excitation of subarrays is studied to provide the ability of doubling the frame rate (FR). To this end, orthogonal chirps, orthogonal frequency division multiplexing method or the same pulse excitation are used in this study to excite the subarrays simultaneously. Although the best resolution is provided in the same-excitation mode, but cross talk (CR) artifact is occurred due to similarity of the excitation pulses. This study shows the dominant CR artifact is concentrated in lower depths and validates this claim with analytical and simulation results. Field II toolbox is used to simulate PSA imaging with 2 subarrays of length 32-element as transmitter and an array of 96-elements as receiver. Some cyst phantoms at depth 20mm to 75mm were simulated. It was shown for this medium's depth, the dominant CR is limited at depths lower than 40mm and at the other depths the same resolution as sequential excitation mode is provided.

Masume Sadeghi

Papers

Double-Stage Delay Multiply and Sum Beamforming Algorithm Applied to Ultrasound Medical Imaging.

Improving beamforming performance by phased synthetic aperture imaging in medical ultrasound

A novel adaptive apodization to improve the resolution of phased subarray imaging in medical ultrasound

Simultaneous excitation of subarrays in ultrasonic Phased Synthetic Aperture imaging in order to improve the frame rate