Ultrasound Imaging System Research Articles

Review on ultrasound-guided photoacoustic imaging for complementary analyses of biological systems in vivo.

Photoacoustic imaging has been developed as a new biomedical molecular imaging modality. Due to its similarity to conventional ultrasound imaging in terms of signal detection and image generation, dual-modal photoacoustic and ultrasound imaging has been applied to visualize physiological and morphological information in biological systems in vivo. By complementing each other, dual-modal photoacoustic and ultrasound imaging showed synergistic advances in photoacoustic imaging with the guidance of ultrasound images. In this review, we introduce our recent progresses in dual-modal photoacoustic and ultrasound imaging systems at various scales of study, from preclinical small animals to clinical humans. A summary of the works reveals various strategies for combining the structural information of ultrasound images with the molecular information of photoacoustic images.

Focused ultrasound neuromodulation of the spleen activates an anti-inflammatory response in humans

Focused ultrasound stimulation (FUS) activates mechanosensitive ion channels and is emerging as a method of noninvasive neuromodulation. In preclinical studies, FUS of the spleen (sFUS) activates an anti-inflammatory neural pathway which suppresses acute and chronic inflammation. However, the relevance of sFUS for regulating inflammatory responses in humans is unknown. Here, we used a modified diagnostic ultrasound imaging system to target the spleen of healthy human subjects with 3 min of continuously swept or stationary focused pulsed ultrasound, delivered at three different energy levels within allowable safety exposure limits. Potential anti-inflammatory effects of sFUS were assessed by measuring sFUS-elicited changes in endotoxin-induced tumor necrosis factor (TNF) production in whole blood samples from insonified subjects. We found that stimulation with either continuously swept or focused pulsed ultrasound has an anti-inflammatory effect: sFUS lowers TNF production for >2 h, with TNF returning to baseline by 24 h following sFUS. This response is independent of anatomical target (i.e., spleen hilum or parenchyma) or ultrasound energy level. No clinical, biochemical, or hematological parameters are adversely impacted. This is the first demonstration that sFUS suppresses the normal inflammatory response in humans, with potential implications for noninvasive bioelectronic therapy of inflammatory disorders.

Beam multiply and sum: A tradeoff between delay and sum and filtered delay multiply and sum beamforming for ultrafast ultrasound imaging

The delay and sum (DAS) has been the popular beamforming algorithm for image reconstruction in ultrafast ultrasound imaging systems due to its low complexity implementation. However, to improve the lower contrast and resolution in images reconstructed using DAS, there have been many adaptive and non-linear beamforming algorithms developed in the recent past. One of the popular non-linear algorithms proposed in the literature, filtered delay multiply and sum (F-DMAS) is sensitive to off-axis clutters and produces artifacts that result in the degradation of the overall image quality along with a possible dynamic range alteration. In this work, a novel approach to combining the strengths of DAS and F-DMAS algorithms is proposed. The proposed approach referred to as beam multiply and sum (BMAS), employs a DAS beamformer in multiple sub-apertures at receive to form the sub-aperture beams and cross multiplies them using a multiply and sum architecture to enhance the spatial coherence and suppress the clutter artifacts. An exhaustive performance comparison in terms of dynamic range alteration, resolution, and contrast of the BMAS is performed with standard in-silico and in-vitro datasets. The results suggest that the proposed approach outperforms the DAS and F-DMAS beamformers in most cases. More than the proposal of a novel beamforming algorithm, to the best of our knowledge, the approach is the first attempt of its kind towards the possibility of the co-existence of two or more beamformers in an ultrasound imaging system. With optimal tuning, it could provide a good trade-off between the effects of improved resolution and improved contrast while keeping the dynamic range linearity unaltered.

Silicate Ions Derived from Calcium Silicate Extract Decelerate Ang II-Induced Cardiac Remodeling.

Pathological cardiac hypertrophy is one of the main activators of heart failure. Currently, no drug can completely reverse or inhibit the development of pathological cardiac hypertrophy. To this end, we proposed a silicate ion therapy based on extract derived from calcium silicate (CS) bioceramics for the treatment of angiotensin II (Ang II) induced cardiac hypertrophy. In this study, the Ang II induced cardiac hypertrophy mouse model was established, and the silicate ion extract was injected to mice intravenously. The cardiac function was evaluated by using a high-resolution Vevo 3100 small animal ultrasound imaging system. Wheat germ Agglutinin, Fluo4-AM staining and immunofluorescent staining was conducted to assess the cardiac hypertrophy, intracellular calcium and angiogenesis of heart tissue, respectively. The in vitro results showed that silicate ions could inhibit the cell size of cardiomyocytes, reduce cardiac hypertrophic gene expression, including atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP) and β-myosin heavy chain (β-MHC), decrease the content of intracellular calcium induced by Ang II. In vivo experiments in mice confirmed that intravenous injection of silicate ions could remarkably inhibit the cardiac hypertrophy and promote the formation of capillaries, further alleviating Ang II-induced cardiac function disorder. This study demonstrated that the released silicate ions from CS possessed potential value as a novel therapeutic strategy of pathological cardiac hypertrophy, which provided a new insight for clinical trials.

Semi‐supervised learning for ABUS tumor detection using deep learning method

AbstractAutomated breast ultrasound (ABUS) imaging system is a practical technique to automatically scan the whole breast. Automatic tumor detection plays a significant role in the clinic. However, training deep convolutional neural networks (CNNs) for tumor detection needs a large quantity of labeled data. It is time‐consuming and expensive to manually annotate tumor positions in ABUS images. In this paper, a novel semi‐supervised learning EfficientDet (SSL‐E) model is proposed for ABUS tumor detection. Our SSL‐E model solves the tumor detection problem from high similarity and serious unbalance between tumors and backgrounds. Considering the image contrast variation and tumor scale variations in ABUS images, color transformation and geometric transformation are employed for data augmentations. Then the consistency between image and its augmented version is developed, thus the robustness of the detector can be improved. Aiming at the problem of serious unbalance between tumors and backgrounds, a novel copy‐paste synthesis strategy is designed, which can generate more tumor samples and enhance tumor diversity. This method is tested on 68 tumor volumes and 68 normal volumes, including 43,248 slices (1683 tumor slices and 41,565 normal slices). It obtains a promising result with sensitivity of 90.2% and false positives per image (FPs/I) at 0.15.

All-digital transmit beamformer for portable high-frequency ultrasound imaging systems.

To meet the requirements of high-frequency ultrasound imaging systems, a transmit-beamforming integrated circuit with higher delay resolution than conventional transmit-beamforming circuits, which are typically implemented using field-programmable gate array chips, is presented. It also requires smaller volumes, allowing for portable applications. Its proposed design includes two all-digital delay-locked loops providing a specified digital control code for a counter-based beamforming delay chain (CBDC) to generate stable and suitable delays for exciting the array transducer elements without variations in process, voltage, and temperature. Moreover, to maintain the duty cycle of long propagation signals, this novel CBDC requires only a few delay cells, significantly reducing hardware costs and power consumption. Simulations were conducted, revealing a maximum time delay of 451.9ns with a time resolution of 652ps and a maximum lateral resolution error of 0.04mm at 6.8mm.

Shear wave elastography (SWE) for the measurement of lens elasticity in the context of monitoring a presbyopia treatment by ultrasonic cavitation

Presbyopia is a progressive loss of accommodation capacity due to a rigidification of the lens. In order to prove the efficiency of ultrasonic cavitation to soften the lens, curvilinear SWE has been developed. It is a method to measure stiffness based on the tracking of surface waves on the outer layer of lens. Experimental models have been implemented: flat phantoms and beads made of 10% and 15% of porcine gelatin and finally porcine lenses (young: 6 months and old: 1 to 6 years). A mechanical vibrator created vibrations (0.1–3.5kHz) and an ultrafast ultrasound imaging system was used to track the propagating waves. From the curvature of the frequency domain of the cross-correlated displacement field, the wavelength and velocity were computed. Experimental models enable to validated the method with dispersion curves substantially different between both concentrations. Results in lenses are similar: a dispersion curve highly dependent of the frequency, reflecting the complexity of elastic wave propagating in a multilayered medium surrounded by a membrane. To retrieve quantitative elasticity data, advanced numerical models have to be developed. This method will be applied on lenses treated by cavitation to assess its potential for treating presbyopia.

Ultrasound-Based Real-Time Imaging of Hydrogel-Based Millirobots with Volume Change Capability

Soft-bodied robots driven by external fields have better environmental adaptability, extending their applications. Nature also provides lots of inspiration for shape-morphing robot development, for example, larvae and jellyfish. This paper presents magnetically propelled hydrogel-based millirobots with volume changeability. The millirobot can be imaged in real time in a completely enclosed space with an ultrasound imaging system. Firstly, a custom-designed magnetic generating system with six square coils was introduced to generate a uniform field to propel the robot. The robot was fabricated using hydrogel with a thickness of around 300 μm. After programmable magnetization, the robot could change its shape and move using the rotating magnetic field. With the near-infrared illumination, the robot could shrink and could recover when the illumination stopped. Even when the robot shrank, it could be propelled by the external field, showing its potential usage in complex environments. Moreover, the posture information of the robot including the position and shape could be obtained in real time using ultrasound image technology.

Sentinel lymph node mapping in patients with breast cancer using a photoacoustic/ultrasound dual-modality imaging system with carbon nanoparticles as the contrast agent: a pilot study.

Assessing the metastatic status of axillary lymph nodes is a common clinical practice in the staging of early breast cancers. Yet sentinel lymph nodes (SLNs) are the regional lymph nodes believed to be the first stop along the lymphatic drainage path of the metastasizing cancer cells. Compared to axillary lymph node dissection, sentinel lymph node biopsy (SLNB) helps reduce morbidity and side effects. Current SLNB methods, however, still have suboptimum properties, such as restrictions due to nuclide accessibility and a relatively low therapeutic efficacy when only a single contrast agent is used. To overcome these limitations, researchers have been motivated to develop a non-radioactive SLN mapping method to replace or supplement radionuclide mapping. We proposed and demonstrated a clinical procedure using a dual-modality photoacoustic (PA)/ultrasound (US) imaging system to locate the SLNs to offer surgical guidance. In our work, the high contrast of PA imaging and its specificity to SLNs were based on the accumulation of carbon nanoparticles (CNPs) in the SLNs. A machine-learning model was also trained and validated to distinguish stained SLNs based on single-wavelength PA images. In the pilot study, we imaged 11 patients in vivo, and the specimens from 13 patients were studied ex vivo. PA/US imaging identified stained SLNs in vivo without a single false positive (23 SLNs), yielding 100% specificity and 52.6% sensitivity based on the current PA imaging system. Our machine-learning model can automatically detect SLNs in real time. In the new procedure, single-wavelength PA/US imaging uses CNPs as the contrast agent. The new system can, with that contrast agent, noninvasively image SLNs with high specificity in real time based on the unique features of the SLNs in the PA images. Ultimately, we aim to use our systems and approach to substitute or supplement nuclide tracers for a non-radioactive, less invasive SLN mapping method in SLNB for the axillary staging of breast cancer.

Total variation‐based ultrasound image despeckling using method noise thresholding in non‐subsampled contourlet transform

AbstractMedical diagnostics rely heavily on ultrasound imaging since it is non‐invasive, inexpensive, and able to provide images in real time. However, the inherent existence of a kind of signal‐dependent noise in these images diminishes the use of ultrasound imaging systems. Speckle noise is inherently present in ultrasound images. Its inherent presence occurs during the image acquisition phase. It decreases the diagnostic usefulness of this imaging modality since it interferes with and reduces the image resolution and contrast. Speckle noise is multiplicative in nature. This multiplicative nature of speckle noise causes adverse effects on ultrasound imaging because it distorts the image quality and causes a loss of the patient's informative content in ultrasound imaging. This causes difficulty in tissue characterization. A lot of research has been done in this field to remove speckle noise while preserving medical information in the image. To handle this issue, research has been grouped into multiple domains. The two main domains include homomorphic and non‐homomorphic filtering. The homomorphic filtering uses a logarithmic transform that converts this multiplicative nature into an additive nature and uses any additive image restoration model to do a despeckling task. Non‐homomorphic filtering encompasses all methods that do not employ a logarithmic transform. Since the presence of speckle noise in ultrasound imaging is an inherent property. Therefore, the despeckling of medical ultrasound images is a mandatory task that cannot be avoided or ignored. This paper proposes a two‐step hybrid and homomorphic despeckling technique, where modified total variation method is applied as step one for speckle reduction purposes. Step two implements method of noise thresholding in the non‐subsampled contourlet transform (NSCT) domain using the bivariate shrinkage rule for edge preservation. The effectiveness and reliability of the proposed method are tested by comparing it with some of the latest methods based on qualitative and quantitative analyses. This paper will help the new researchers understand various problems and their solutions related to ultrasound image despeckling.

Super-resolution ultrasonic Lamb wave imaging based on sign coherence factor and total focusing method

Improving the resolution of ultrasound array imaging systems for multiple defects in a measured medium is a popular research topic in nondestructive testing technology. However, because of the diffraction of acoustic waves, the resolution of ultrasound array imaging systems must follow Rayleigh's criterion and hence is limited, and defects with a spacing smaller than the resolution limit cannot be identified using conventional ultrasound imaging methods. Ultrasonic Lamb waves have dispersion and mode conversion characteristics, and the scattering acoustic field after the interaction between Lamb waves and defects is usually complex, making it even more difficult to improve the imaging resolution. In this paper, ultrasonic Lamb wave imaging is investigated with the sign coherence factor-total focusing method (SCF-TFM) when the spacing of the detected defects is smaller than the resolution limit, and the imaging resolution limit of SCF-TFM is analyzed. Experiments on a single blind-hole defect show that the lateral resolution of the SCF-TFM imaging is nearly twice as high as that of the total focusing method (TFM), with a higher signal-to-noise ratio. For experiments on multiple blind-hole defects, the resolution of the SCF-TFM improves by 71.32%, which is higher than that of the TFM when the spacing of the detected defects is larger than the resolution limit. The SCF-TFM enables super-resolution imaging and achieves a higher resolution limit than time-domain topological energy when the spacing of the detected defects is smaller than the resolution limit.

乳房用リング型超音波画像診断装置の現状と展望について

乳房用リング型超音波画像診断装置の現状と展望について

Wide-field three-dimensional photoacoustic/ultrasound scanner using a two-dimensional matrix transducer array.

Two-dimensional matrix transducer arrays are the most appropriate imaging probes for acquiring dual-modal 3D photoacoustic (PA)/ultrasound (US) images. However, they have small footprints which limit the field-of-view (FOV) to less than 10 mm × 10 mm and degrade the spatial resolution. In this study, we demonstrate a dual-modal PA and US imaging system (using a 2D matrix transducer array and a motorized 2D scanning system) to enlarge the FOV of volumetric images. Multiple PA volumes were merged to form a wide-field image of approximately 45 mm × 45 mm. In vivo imaging was demonstrated using rat sentinel lymph nodes (SLNs) and bladders stained with methylene blue. We believe that this volumetric PA/US imaging technique with a 2D matrix transducer array can be a useful tool for narrow-field real-time monitoring and wide-field imaging of various preclinical and clinical studies.

Liver Tumors Segmentation Using 3D SegNet Deep Learning Approach

An ultrasonic filter detects signs of malignant tumors by analysing the image’s pixel quality fluctuations caused by a liver ailment. Signs of malignant growth proximity are identified in an ultrasound filter through image pixel quality variations from a liver’s condition. Those changes are more common in alcoholic liver conditions than in other etiologies of cirrhosis, suggesting that the cause may be alcohol instead of liver disease. Existing Two-Dimensional (2D) ultrasound data sets contain an accuracy rate of 85.9% and a 2D Computed Tomography (CT) data set of 91.02%. The most recent work on designing a Three-Dimensional (3D) ultrasound imaging system in or close to real-time is examined. In this article, a Deep Learning (DL) model is implemented and modified to fit liver CT segmentation, and a semantic pixel classification of road scenes is recommended. The architecture is called semantic pixel-wise segmentation and comprises a hierarchical link of encoder-decoder layers. A standard data set was used to test the proposed model for liver CT scans and the tumor accuracy in the training phase. For the normal class, we obtained 100% precision for chronic cirrhosis hepatitis (73%), offset cirrhosis (59.26%), and offensive cirrhosis (91.67%) for chronic hepatitis or cirrhosis (73,0%). The aim is to develop a Computer-Aided Detection (CAD) screening tool to detect steatosis. The results proved 98.33% exactness, 94.59% sensitivity, and 92.11% case with Convolutional Neural Networks (CNN) classification. Although the classifier’s performance did not differentiate so clearly at this level, it was recommended that CNN generally perform better due to the good relationship between Area under the Receiver Operating Characteristics Curve (AUC) and accuracy.

Tunable image quality control of 3-D ultrasound using switchable CycleGAN.

In contrast to 2-D ultrasound (US) for uniaxial plane imaging, a 3-D US imaging system can visualize a volume along three axial planes. This allows for a full view of the anatomy, which is useful for gynecological (GYN) and obstetrical (OB) applications. Unfortunately, the 3-D US has an inherent limitation in resolution compared to the 2-D US. In the case of 3-D US with a 3-D mechanical probe, for example, the image quality is comparable along the beam direction, but significant deterioration in image quality is often observed in the other two axial image planes. To address this, here we propose a novel unsupervised deep learning approach to improve 3-D US image quality. In particular, using unmatched high-quality 2-D US images as a reference, we trained a recently proposed switchable CycleGAN architecture so that every mapping plane in 3-D US can learn the image quality of 2-D US images. Thanks to the switchable architecture, our network can also provide real-time control of image enhancement level based on user preference, which is ideal for a user-centric scanner setup. Extensive experiments with clinical evaluation confirm that our method offers significantly improved image quality as well user-friendly flexibility.

A Hybrid Boost Converter With Standard CMOS-Compatible 14-V Output for an Ultrasound Imaging System

This paper presents a hybrid boost converter that achieves a 14V regulated output and multiple intermediate voltage levels in standard CMOS, targeted for an ultrasound imaging system (UIS) application. The intermediate voltage levels are regulated at 3.5V, 7V, 10.5V from a 1.5V input. For ease of integration with existing intellectual properties (IPs) and for digital back end (DBE) integration flexibility, all switch stresses are kept within 3.5V for standard CMOS compatibility. Implemented in 180nm 1P6M standard CMOS process, the hybrid boost converter achieves efficiency of 78%.

A New Fast Logarithm Algorithm Using Advanced Exponent Bit Extraction for Software-Based Ultrasound Imaging Systems

Ultrasound B-mode imaging provides anatomical images of the body with a high resolution and frame rate. Recently, to improve its flexibility, most ultrasound signal and image processing modules in modern ultrasound B-mode imaging systems have been implemented in software. In a software-based B-mode imaging system, an efficient processing technique for calculating a logarithm instruction is required to support its high computational burden. In this paper, we present a new method to efficiently implement a logarithm operation based on exponent bit extraction. In the proposed method, the exponent bit field is first extracted and then some algebraic operations are applied to improve its precision. To evaluate the performance of the proposed method, the peak signal-to-noise ratio (PSNR) and the execution time were measured. The proposed efficient logarithm operation method substantially reduced the execution time, i.e., eight times, compared to direct computation while providing a PSNR of over 50 dB. These results indicate that the proposed efficient logarithm computation method can be used for lowering the computational burden in software-based ultrasound B-mode ultrasound imaging systems while improving or maintaining the image quality.

A High-Frequency Mechanical Scanning Ultrasound Imaging System

High-frequency ultrasound has developed rapidly in clinical fields such as cardiovascular, ophthalmology, and skin with its high imaging resolution. However, the development of multi-elements high-frequency ultrasonic transducers and multi-channel high-frequency ultrasound imaging systems is extremely challenging. Here, a high-frequency ultrasound imaging system based on mechanical scanning was proposed in this paper. It adopts the method of reciprocating feed mechanism, which can achieve reciprocating scanning in the 14 mm range at 168 mm/s with a small 60 MHz transducer. A single-channel high-frequency ultrasonic imaging system consisting of the transmitting module, analog front end, acquisition module, and FPGA control module was developed. To overcome the non-uniformity of mechanical scanning, the ultrasound images are compensated according to the motion trajectory. The wire target and ex vivo tissue experiments have shown that the system can obtain an imaging resolution of 51 μm, imaging depth of 8 mm, and imaging speed of 12 fps. This high-frequency mechanical scanning ultrasound imaging system has the characteristics of simple structure, high-frequency, real-time, and good imaging performance, which can meet the clinical needs of high-resolution ultrasound images.

Improving Image Quality by Deconvolution Recovery Filter in Ultrasound Imaging.

Due to the advantages of non-radiation and real-time performance, ultrasound imaging is essential in medical imaging. Image quality is affected by the performance of the transducer in an ultrasound imaging system. For example, the bandwidth controls the pulse length, resulting in different axial resolutions. Therefore, a transducer with a large bandwidth helps to improve imaging quality. However, large bandwidths lead to increased system cost and sometimes a loss of sensitivity and lateral resolution in attenuating media. In this paper, a deconvolution recovery method combined with a frequency-domain filtering technique (DRF) is proposed to improve the imaging quality, especially for the axial resolution. In this method, the received low-bandwidth echo signals are converted into high-bandwidth signals, which is similar to the echo signals produced by a high-bandwidth transducer, and the imaging quality is improved. Simulation and experiment results show that, compared with Delay-and-sum (DAS) method, the DRF method improved axial resolution from 0.60 to 0.41 mm in simulation and from 0.62 to 0.47 mm in the tissue-mimicking phantom experiment. The contrast ratio performance is improved to some extent compared with the DAS in experimental and in-vivo images. Besides, the proposed method has the potential to further improve image quality by combining it with adaptive weightings, such as the minimum variance method.

Fabrication, Acoustic Characterization and Phase Reference-Based Calibration Method for a Single-Sided Multi-Channel Ultrasonic Actuator.

The ultrasonic actuator can be used in medical applications because it is label-free, biocompatible, and has a demonstrated history of safe operation. Therefore, there is an increasing interest in using an ultrasonic actuator in the non-contact manipulation of micromachines in various materials and sizes for therapeutic applications. This research aims to design, fabricate, and characterize a single-sided transducer array with 56 channels operating at 500 kHz, which provide benefits in the penetration of tissue. The fabricated transducer is calibrated using a phase reference calibration method to reduce position misalignment and phase discrepancies caused by acoustic interaction. The acoustic fields generated by the transducer array are measured in a 300 mm × 300 mm × 300 mm container filled with de-ionized water. A hydrophone is used to measure the far field in each transducer array element, and the 3D holographic pattern is analyzed based on the scanned acoustic pressure fields. Next, the phase reference calibration is applied to each transducer in the ultrasonic actuator. As a result, the homogeneity of the acoustic pressure fields surrounding the foci area is improved, and the maximum pressure is also increased in the twin trap. Finally, we demonstrate the capability to trap and manipulate micromachines with acoustic power by generating a twin trap using both optical camera and ultrasound imaging systems in a water medium. This work not only provides a comprehensive study on acoustic actuators but also inspires the next generation to use acoustics in medical applications.