Inaccurate placement of the ablation catheter and the inability to monitor the real-time temperature within the tissue of interest such as veins curbs the treatment efficacy of laser ablation procedures during thermal therapies. Our previous studies have validated the efficacy of photoacoustic (PA) imaging during endovenous laser ablation (EVLA) procedures. However, the PA-guided therapies suffer from

Portable ultrasound has been extensively used for diagnostic applications in health monitoring, emergency rooms, and ambulances. However, these handheld ultrasound systems may suffer from heat and battery issues attributed to the large power consumption of the transmitter. Additionally, the largest portion of the direct current (DC) power consumption can be attributed to the amplifier in the digital-to-analog

Portable ultrasound has been extensively used for diagnostic applications in health monitoring, emergency rooms, and ambulances. However, these handheld ultrasound systems may suffer from heat and battery issues attributed to the large power consumption of the transmitter. Additionally, the largest portion of the direct current (DC) power consumption can be attributed to the amplifier in the digital-to-analog

Chronic kidney disease (CKD) is characterized by progressive reductions in skeletal muscle function and size. The concept of muscle quality is increasingly being used to assess muscle health, although the best means of assessment remains unidentified. The use of muscle echogenicity is limited by an inability to be compared across devices. Gray level of co-occurrence matrix (GLCM), a form of image texture

Ultrasonic guided wave techniques have been applied to characterize cortical bone for osteoporosis assessment. Compared with the current gold-standard X-ray-based diagnostic methods, ultrasound-based techniques pose some advantages such as compactness, low cost, lack of ionizing radiation, and their ability to detect the mechanical properties of the cortex. Axial transmission technique with a source-receiver

Significant successes in machine learning approaches to image analysis for various applications have energized strong interest in automated diagnostic support systems for medical images. The evolving in-depth understanding of the way carcinogenesis changes the texture of cellular networks of a mass/tumor has been informing such diagnostics systems with use of more suitable image texture features and

The quality assurance (QA) of ultrasound transducers is often identified as an area requiring continuous development in terms of the tools available to users. Periodic evaluation of the transducers as part of the QA protocol is important, since the quality of the diagnostics. Some of the key criteria determining the process of developing a QA protocol include the complexity of setup, the time required

In this study, an automatic pennation angle measuring approach based on deep learning is proposed. Firstly, the Local Radon Transform (LRT) is used to detect the superficial and deep aponeuroses on the ultrasound image. Secondly, a reference line are introduced between the deep and superficial aponeuroses to assist the detection of the orientation of muscle fibers. The Deep Residual Networks (Resnets)

Quantitative ultrasound techniques have been previously used to evaluate biological hard tissues, characterized by a large acoustic impedance contrast. Here, we are interested in the imaging of experimental data from different test-targets with high acoustic impedance contrast, using the Full Waveform Inversion (FWI) method to solve the inverse problem. This method is based on high-resolution numerical

Spatial frequency analysis (SFA) is a quantitative ultrasound method that characterizes tissue organization. SFA has been used for research involving tendon injury, but may prove useful in similar research involving skeletal muscle. As a first step, we investigated if SFA could detect known architectural differences within hamstring muscles. Ultrasound B-mode images were collected bilaterally at locations

In the clinical analysis of Intravascular ultrasound (IVUS) images, the lumen size is an important indicator of coronary atherosclerosis, and is also the premise of coronary artery disease diagnosis and interventional treatment. In this study, a fully automatic method based on deep learning model and handcrafted features is presented for the detection of the lumen borders in IVUS images. First, 193

Minimum-variance (MV) beamforming, as a typical adaptive beamforming method, has been widely studied in medical ultrasound imaging. This method achieves higher spatial resolution than traditional delay-and-sum (DAS) beamforming by minimizing the total output power while maintaining the desired signals. However, it suffers from high computational complexity due to the heavy calculation load when determining

Nipple is a vital landmark in the breast lesion diagnosis. Although there are advanced computer-aided detection (CADe) systems for nipple detection in breast mediolateral oblique (MLO) views of mammogram images, few academic works address the coronal views of breast ultrasound (BUS) images. This paper addresses a novel CADe system to locate the Nipple Shadow Area (NSA) in ultrasound images. Here the

It is of vital importance to identify the pleural line when performing lung ultrasound, as the pleural line not only indicates the interface between the chest wall and lung, but offers additional diagnostic information. In the current clinical practice, the pleural line is visually detected and evaluated by clinicians, which requires experiences and skills with challenges for the novice. In this study

Photoacoustic signal recorded by photoacoustic imaging system can be modeled as convolution of initial photoacoustic response by the photoacoustic absorber with the system impulse response. Our goal was to compute the size of photoacoustic absorber using the initial photoacoustic response, deconvolved from the recorded photoacoustic data. For deconvolution, we proposed to use the impulse response of

To explore the value of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of molecular subtypes of breast cancer. Sixty-two cases of breast cancer were divided into luminal epithelium A or B subtype (luminal A/B), Her-2 over-expression subtype and triple negative subtype (TN). CEUS and routine ultrasonography were performed for all patients before surgery. (1) The luminal epithelium

Ultrasound images, having low contrast and noise, adversely impact in the detection of abnormalities. In view of this, an enhancement method is proposed in this work to reduce noise and improve contrast of ultrasound images. The proposed method is based on scaling with neutrosophic similarity score (NSS), where an image is represented in the neutrosophic domain through three membership subsets T, I

The intima media thickness (IMT) of the common carotid artery (CCA) can be used to predict the risk of atherosclerosis. Many image segmentation techniques have been used for IMT measurement. However, severe noise in the ultrasound image can lead to erroneous segmentation results. To improve the robustness to noise, a fully automatic method, based on an improved Otsu’s method and an adaptive wind-driven

Carotid plaque segmentation in ultrasound longitudinal B-mode images using deep learning is presented in this work. We report on 101 severely stenotic carotid plaque patients. A standard U-Net is compared with a dilated U-Net architecture in which the dilated convolution layers were used in the bottleneck. Both a fully automatic and a semi-automatic approach with a bounding box was implemented. The

Muscle fatigue often occurs over a long period of exercise, and it can increase the risk of muscle injury. Evaluating the state of muscle fatigue can avoid unnecessary overtraining and injury of the muscle. Ultrasound imaging can non-invasively visualize muscle tissue in real-time. Image entropy is commonly used to characterize the texture of an image. In this study, we evaluated changes in the ultrasound

Breast cancer ranks first among cancers affecting women’s health. Our work aims to realize the intelligence of the medical ultrasound equipment with limited computational capability, which is used for the assistant detection of breast lesions. We embed the high-computational deep learning algorithm into the medical ultrasound equipment with limited computational capability by two techniques: (1) lightweight

We aimed to use deep learning with convolutional neural networks (CNNs) to discriminate images of benign and malignant breast masses on ultrasound shear wave elastography (SWE). We retrospectively gathered 158 images of benign masses and 146 images of malignant masses as training data for SWE. A deep learning model was constructed using several CNN architectures (Xception, InceptionV3, InceptionResNetV2

After 100 years of theoretical treatment of speckle patterns from coherent illumination, there remain some open questions about the nature of ultrasound speckle from soft vascularized tissues. A recent hypothesis is that the fractal branching vasculature is responsible for the dominant echo pattern from organs such as the liver. In that case, an analysis of cylindrical scattering structures arranged

It is known that the elasticity of liver reduces progressively in the case of diffuse liver disease. Currently, the diagnosis of diffuse liver disease requires a biopsy, which is an invasive procedure. In this paper, we evaluate and report a noninvasive method that can be used to quantify liver stiffness using quasi-static ultrasound elastography approach. Quasi-static elastography is popular in clinical

We perform finite element modeling of pulse-echo ultrasound of a hard inclusion in a soft tissue to gain a better understanding of B-mode image brightness characteristics. We simulate a pressure wave emitted by an ultrasound transducer through the inclusion-tissue medium by prescribing suitable boundary conditions, and collect the scattered wave response to simulate the behavior of the transducer array

Because of continuous movement and variation in diameter of the inferior vena cava (IVC) with respiration, the measurements on IVC are labor-intensive and with considerable inter-operator variations. Some computer-assisted techniques have been developed to track the movement of the IVC semi-automatically. However, existing methods predominantly rely on reference marker selection and require many manual

Fibromyalgia (FM) diagnosis remains a challenge for clinicians due to a lack of objective diagnostic tools. One proposed solution is the use of quantitative ultrasound (US) techniques, such as image texture analysis, which has demonstrated discriminatory capabilities with other chronic pain conditions. From this, we propose the use of image texture variables to construct and compare two machine learning

The temporal super-resolution of the dynamic ultrasound imaging, a means to observe rapid heart movements, is considered an important subject in medical diagnosis of cardiac conditions. Here, a new technique based on the acquisition scheme using the matrix completion (MC) theory is offered for the temporal super-resolution of the two-dimensional (2D) and three-dimensional (3D) ultrasound imaging. MC

Early detection and diagnosis of liver fibrosis is of critical importance. Currently the gold standard for diagnosing liver fibrosis is biopsy. However, liver biopsy is invasive and associated with sampling errors and can lead to complications such as bleeding. Therefore, developing noninvasive imaging techniques for assessing liver fibrosis is of clinical value. Ultrasound has become the first-line

Accurate tracking of tissue motion is critically important for several ultrasound elastography methods. In this study, we investigate the feasibility of using three published convolution neural network (CNN) models built for optical flow (hereafter referred to as CNN-based tracking) by the computer vision community for breast ultrasound strain elastography. Elastographic datasets produced by finite

Complete and accurate separation of harmonic components from the ultrasonic radio frequency (RF) echo signals is essential to improve the quality of harmonic imaging. There are limitations in the existing two commonly used separation methods, that is, the subjectivity for the high-pass filtering (S_HPF) method and motion artifacts for the pulse inversion (S_PI) method. A novel separation method called

Ultrasound poroelastography is a cost-effective and noninvasive imaging technique, which can be used to reconstruct mechanical parameters of tissues such as Young's modulus, Poisson's ratio, interstitial permeability, and vascular permeability. To estimate interstitial permeability and vascular permeability using poroelastography, accurate estimation of the strain time constant (TC) is required. This

In conventional linear array (CLA)-based elastography tissue compression in one direction (e.g., axial) leads to an expansion in all other directions (lateral, elevation). Therefore, the estimation of the lateral displacements and strains may provide additional information on the tissue mechanical properties. However, these are not exploited fully due to the inherent limitation in lateral sampling

Ultrasonic coda wave analysis techniques localize defects in fields such as seismography and nondestructive testing. In medical ultrasound, these techniques might provide novel mapping of tissue properties in diseases characterized by local fibrosis. In this work, we present an approach for localizing variation in scattering properties in the diffuse regime with an array transducer in medical ultrasound

High-frame-rate ultrasound is an emerging technique for functional ultrasound imaging. However, the lateral spatial resolution and contrast in high-frame-rate ultrasound with an unfocused transmit beam are inherently lower than those in conventional ultrasonic imaging based on the line-by-line acquisition using a focused ultrasonic beam because of the low directivity of the transmit beam. Coherence-based

Echodynamography (EDG) is a computational method to estimate and visualize two-dimensional flow velocity vectors by applying dynamic flow theories to color Doppler echocardiography. The EDG method must be validated if applied to human cardiac flow function. However, a few studies of flow estimated have compared by EDG to the flow data were acquired by other methods. In this study, EDG was validated

Breast cancer has become the biggest threat to female health. Ultrasonic diagnosis of breast cancer based on artificial intelligence is basically a classification of benign and malignant tumors, which does not meet clinical demand. Besides, the current target detection method performs poorly in detecting small lesions, while it is clinically required to detect nodules below 2 mm. The objective of this

Photoacoustic imaging (PAI) is an emerging biomedical imaging technique that utilizes a combination of light and ultrasound to detect photoabsorbers embedded within tissues. While the clinical utility of PAI has been widely explored for several applications, limitations in light penetration and detector sensitivity have restricted these studies to mostly superficial sites. Given the importance of PA

B-mode ultrasound is an essential part of radiological examinations due to its low cost, safety, and portability, but has the drawbacks of the speckle noise and output of most systems is two-dimensional (2D) cross sections. Image restoration techniques, using mathematical models for image degradation and noise, can be used to boost resolution (deconvolution) as well as to reduce the speckle. In this

Peripheral artery disease is often asymptomatic, and various imaging and nonimaging techniques have been used for assessment and monitoring treatments. This study is designed to demonstrate the ability of photoacoustic imaging to noninvasively determine changes in tissue oxygenation that occur in mice's hind limb skeletal muscle as they age. Mice from two age cohorts were scanned bilaterally with a

Double-stage delay-multiply-and-sum (DS-DMAS) is an algorithm proposed for photoacoustic image reconstruction. The DS-DMAS algorithm offers a higher contrast than conventional delay-and-sum and delay-multiply and-sum but at the expense of higher computational complexity. Here, we utilized a compute unified device architecture (CUDA) graphics processing unit (GPU) parallel computation approach to address

The ultrasonic backscatter technique holds the promise of characterizing bone density and microstructure. This paper conducts ultrasonic backscatter parametric imaging based on measurements of apparent integrated backscatter (AIB), spectral centroid shift (SCS), frequency slope of apparent backscatter (FSAB), and frequency intercept of apparent backscatter (FIAB) for representing trabecular bone mass

Measurement of corneal biomechanical properties can aid in predicting corneal responses to diseases and surgeries. For delineation of spatially resolved distribution of corneal elasticity, high-resolution elastography system is required. In this study, we demonstrate a high-resolution elastography system using high-frequency ultrasound for ex-vivo measurement of intraocular pressure (IOP)-dependent

Intravascular ultrasound (IVUS) is an important diagnostic method for coronary disease. The lateral and axial resolutions of IVUS systems under study are typically ~120 and ~30 µm, respectively. The lateral resolution has a lower quality than the axial one and is restricted by the aperture size of transducers. In addition, this resolution is difficult to further improve physically. However, IVUS is

To perform computer-aided diagnosis of the thyroid nodules on ultrasound images, the location and boundary of nodules should be clearly defined. However, the identification of thyroid nodule boundary is a difficult issue due to the biological characteristics of the nodules, the physics and quality of ultrasound imaging, and the subjective factors and operating conditions of the operator. In this study

Research involving B-mode ultrasound imaging often requires user defined regions of interest (ROIs) for analysis, traditionally drawn/selected by a trained operator. This manual process is incredibly time consuming and subjective. Here, we propose a fast and simple method of detecting the average location of aponeurosis layers in ultrasound images of the upper trapezius to place a rectangular ROI for

With the development of integrated circuit (IC) technologies, complex transmitting and receiving circuits can be integrated into miniature intravascular ultrasound (IVUS) catheters, making it possible to adopt better synthesizing schemes for better imaging. Eccentric cylinder wave compounding should be an optimum synthesizing scheme for the small size cylinder shaped catheter. Eccentric cylinder waves

This retrospective study aimed to use preoperative and contrast-enhanced ultrasound (CEUS) factors to assess and reveal risk factors of early recurrence (ER) in patients with hepatocellular carcinoma (HCC). We enrolled 141 patients with primary HCC who had undergone surgical resection. The assessment of the CEUS scan includes (a) the maximum diameter of the lesion, (b) the tumor echogenicity of gray-scale

The detection of the media-adventitia (MA) border in intravascular ultrasound (IVUS) images is essential for vessel assessment and disease diagnosis. However, it remains a challenging task, considering the existence of plaque, calcification, and various artifacts. In this article, an effective method based on classification is proposed to extract the MA border in IVUS images. First, a novel morphologic

The aim of this study was to identify independent risk factors for thyroid cancer, establish an ultrasonographic multimodality diagnostic model for thyroid nodules, and explore the diagnostic value of the model. From November 2011 to February 2015, 307 patients with a total of 367 thyroid nodules underwent conventional ultrasound, contrast-enhanced ultrasound (CEUS), and ultrasound elastography examinations

Subharmonic-aided pressure estimation (SHAPE) estimates hydrostatic pressure using the inverse relationship with subharmonic amplitude variations of ultrasound contrast agents (UCAs). We studied the impact of varying incident acoustic outputs (IAO), UCA concentration, and hematocrit on SHAPE. A Logiq 9 scanner with a 4C curvilinear probe (GE, Milwaukee, Wisconsin) was used with Sonazoid (GE Healthcare

We describe the concept of a new imaging modality based on the tracking and dynamic modeling of local intensity changes (ICs) observed in conventional ultrasound images collected during a medium-temperature change. We computed the pixel-by-pixel IC from averaged B-mode images that exhibited different behaviors with varying temperature resulting from changes in the speed of sound, which consequently

Phase aberration is a phenomenon caused by heterogeneity of the speed of sound in tissue, in which the actual speed of sound of the tissue is different than the assumed speed of sound used for beamforming. It reduces the quality and resolution of ultrasonic images and impairs clinical diagnostic capabilities. Although phase aberration correction (PAC) methods can reduce these detrimental effects, most

Sound speed is an effective parameter in designing an optimal beamformer. In conventional ultrasound imaging systems, the beamformer is designed assuming a fixed value of speed, whereas the speed in a tissue is not known precisely and also may fluctuate by a great value. The errors in estimating sound speed may lead to a severe degradation in the reconstructed image, as mainlobe width and sidelobe

Across the varieties of waves that have been studied in physics, it is well established that group velocities can be significantly greater than or less than phase velocities measured within comparable frequency bands, depending on the particular mechanisms involved. The distinction between group and phase velocities is important in elastography, because diagnoses are made based on shear wave speed

Shear wave imaging is considered to be more precise and less operator dependent when compared with strain imaging. It enables quantitative and reproducible data (Young's modulus of the imaged tissue). However, results of shear wave imaging can be affected by a variety of different factors. The aim of this study is to evaluate the effect of the pressure applied by the ultrasound probe during examination

Chronic liver diseases are fifth leading cause of fatality in developing countries. Their early diagnosis is extremely important for timely treatment and salvage life. To examine abnormalities of liver, ultrasound imaging is the most frequently used modality. However, the visual differentiation between chronic liver and cirrhosis, and presence of heptocellular carcinomas (HCC) evolved over cirrhotic

Tumor microvascularization is a biomarker of response to antiangiogenic treatments and is accurately assessed by ultrasound imaging. Imaging modes used to visualize slow flows include Power Doppler imaging, dynamic contrast-enhanced ultrasonography, and more recently, microvascular Doppler. Flow phantoms are used to evaluate the performance of Doppler imaging techniques, but they do not have a steady

Ultrasound measurement of the inferior vena cava (IVC) is widely implemented in the clinic. However, the process is time consuming and labor intensive, because the IVC diameter is continuously changing with respiration. In addition, artificial errors and intra-operator variations are always considerable, making the measurement inconsistent. Research efforts were recently devoted to developing semiautomated