Abstract:Delay‐and‐sum (DAS) is one of the most common algorithms used to construct the photoacoustic images due to its low complexity. However, it results in images with high sidelobes and low resolution. Delay‐and‐standard‐deviation (DASD) weighting factor can improve the contrast of the images compared to DAS. However, it still suffers from high sidelobes. In this work, a new weighting factor, named delay‐multiply‐and‐standard‐deviation (DMASD) is introduced to enhance the contrast of the reconstructed images compar… Show more
“…The theoretical values for axial and lateral resolutions [46] were calculated as 299 μm and 300 μm for US images, and 211 μm and 300 μm for PA images respectively, which are in full compliance with the experimental measurements. We believe that by employing more advanced beamforming algorithms, such as using synthetic aperture techniques, coherence factor weighting, and weighting beamforming, the quality of images could be further improved [[47], [48], [49], [50]]. Fig.…”
Visualization and detection of early-stage gynecological malignancies represents a challenge for imaging due to limiting factors including tissue accessibility, device ease of use, and accuracy of imaging modalities. In this work, we introduce a miniaturized phased-array ultrasound and photoacoustic endoscopic probe which is capable of providing structural, functional, and molecular data for the characterization of gynecologic disease. The proposed probe consists of a 64-element ultrasound phased-array transducer coupled to a fiber-optic light delivery system for co-registered ultrasound and photoacoustic imaging. The fabricated US and PA imaging endoscope’s diameter is 7.5 mm, allowing for potential passage through the cervical canal and thus an intimate contact with gynecological tissues such as the cervical canal and uterus. The developed endoscopic probe was tested and characterized in a set of tissue-mimicking phantoms. US and PA resolutions were measured experimentally using 200 μm diameter wires, resulting in apparent axial and lateral diameters of 289 μm and 299 μm for US, and 308 μm and 378 μm for PA, respectively. The probe’s abilities to operate in both discrete and integrated illumination/acquisition were tested in gelatin phantoms with embedded optical absorbers with the results demonstrating the ability to acquire volumetric dual-modal US and PA images.
“…The theoretical values for axial and lateral resolutions [46] were calculated as 299 μm and 300 μm for US images, and 211 μm and 300 μm for PA images respectively, which are in full compliance with the experimental measurements. We believe that by employing more advanced beamforming algorithms, such as using synthetic aperture techniques, coherence factor weighting, and weighting beamforming, the quality of images could be further improved [[47], [48], [49], [50]]. Fig.…”
Visualization and detection of early-stage gynecological malignancies represents a challenge for imaging due to limiting factors including tissue accessibility, device ease of use, and accuracy of imaging modalities. In this work, we introduce a miniaturized phased-array ultrasound and photoacoustic endoscopic probe which is capable of providing structural, functional, and molecular data for the characterization of gynecologic disease. The proposed probe consists of a 64-element ultrasound phased-array transducer coupled to a fiber-optic light delivery system for co-registered ultrasound and photoacoustic imaging. The fabricated US and PA imaging endoscope’s diameter is 7.5 mm, allowing for potential passage through the cervical canal and thus an intimate contact with gynecological tissues such as the cervical canal and uterus. The developed endoscopic probe was tested and characterized in a set of tissue-mimicking phantoms. US and PA resolutions were measured experimentally using 200 μm diameter wires, resulting in apparent axial and lateral diameters of 289 μm and 299 μm for US, and 308 μm and 378 μm for PA, respectively. The probe’s abilities to operate in both discrete and integrated illumination/acquisition were tested in gelatin phantoms with embedded optical absorbers with the results demonstrating the ability to acquire volumetric dual-modal US and PA images.
“…Standard deviation (SD) is a statistical concept, which has been widely used in many fields. Such as in [33], standard deviation was used into industrial equipment to help process the signal of bubble detection in liquid sodium; in [34], standard deviation is used with delay multiply to form a new weighting factor, which is introduced to enhance the contrast of the reconstructed images in medical fields; in [35], based on eight-year-old dental trauma research data, standard deviation was utilized to help analyze the potential of laser Doppler flowmetry; the beam forming performance has a large impact on image quality in ultrasound imaging, to improve image resolution and contrast; in [36], a new adaptive weighting factor for ultrasound imaging called signal mean-to-standard-deviation factor (SMSF) was proposed, based on which researchers put forward an adaptive beam forming method for ultrasound imaging based on the mean-to-standard-deviation factor; in [37], standard deviation was adopted to help analyze when an individual should start social security.…”
Section: Standard Deviation Updating Amount (Sdua)mentioning
To improve the optimization quality, stability, and speed of convergence of wolf pack algorithm, an adaptive shrinking grid search chaotic wolf optimization algorithm using standard deviation updating amount (ASGS-CWOA) was proposed. First of all, a strategy of adaptive shrinking grid search (ASGS) was designed for wolf pack algorithm to enhance its searching capability through which all wolves in the pack are allowed to compete as the leader wolf in order to improve the probability of finding the global optimization. Furthermore, opposite-middle raid method (OMR) is used in the wolf pack algorithm to accelerate its convergence rate. Finally, “Standard Deviation Updating Amount” (SDUA) is adopted for the process of population regeneration, aimed at enhancing biodiversity of the population. The experimental results indicate that compared with traditional genetic algorithm (GA), particle swarm optimization (PSO), leading wolf pack algorithm (LWPS), and chaos wolf optimization algorithm (CWOA), ASGS-CWOA has a faster convergence speed, better global search accuracy, and high robustness under the same conditions.
“…The dynamic CF (DCF) based on the ASD [35] has been proposed for CPWC imaging, showing overall improvements in image quality over CF. The delay-multiply-and-standard-deviation (DMASD) factor based on the delay and standard deviation (DASD) beamforming [36], which uses the ASD of echo signals, was introduced to enhance the image contrast [37]. In addition, the ASD has also been studied to reduce the dark-region artifacts introduced by ESBMV in CPWC imaging [38].…”
Coherent plane-wave compounding (CPWC) enables high-frame-rate ultrasound imaging, but the imaging quality is mainly determined by the beamforming method. Covariance-matrix-based statistical beamforming (CMSB) was previously proposed for synthetic aperture ultrasound imaging, which provides notable improvements in resolution and contrast over conventional delay-and-sum (DAS). However, the speckle quality is inadequate in the phantom experiment, and there exists a tradeoff between the contrast and speckle preservation of CMSB due to the constant diagonal reducing factor. In this paper, we applied CMSB in CPWC ultrasound imaging and propose an enhanced CMSB approach for CPWC to enhance the image quality. First, we introduced lag-one coherence (LOC) as an adaptive weighting factor for CMSB to suppress incoherent noise. Then, we propose adaptive diagonal reducing for CMSB using the coherence factor and amplitude standard deviation, with the aim to further improve the speckle quality. Finally, the combination of LOC weighting and adaptive diagonal reducing is proposed for CMSB to simultaneously improve the contrast and speckle quality. A simulation, experiments, and carotid studies were used to validate the imaging performance of the proposed methods. Results from the experiments show that LOC-weighted CMSB (LOCw-CMSB) with adaptive diagonal reducing improves the average contrast, generalized contrast-to-noise ratio (gCNR), and speckle signal-to-noise ratio (sSNR) by 59.9%, 53.6%, and 77.7%, respectively, in comparison with DMAS. The contrast and sSNR of the LOCw-CMSB with adaptive diagonal reducing were improved by 32.3% and 33.1%, respectively, compared to CMSB. In addition, LOCw-CMSB with adaptive diagonal reducing improves the contrast by 176.6% compared with SLSC in the in vivo carotid study, while it obtains a comparable gCNR. These results demonstrate that the proposed methods are effective in improving the image quality of CPWC imaging.
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