Ultrasonic backscatter characterization of cancellous bone using a general Nakagami statistical model

The goal of this study is to analyze the statistics of the backscatter signal from bovine cancellous bone using a Nakagami model and to evaluate the feasibility of Nakagami-model parameters for cancellous bone characterization. Ultrasonic backscatter measurements were performed on 24 bovine cancellous bone specimens in vitro and the backscatter signals were compensated for the frequency-dependent attenuation prior to the envelope detection. The statistics of the backscatter envelope were modeled using the Nakagami distribution. Our results reveal that the backscatter envelope mainly followed pre-Rayleigh distributions, and the deviations of the backscatter envelope from Rayleigh distribution decreased with increasing bone density. The Nakagami shape parameter(i.e., m) was significantly correlated with bone densities(R = 0.78–0.81, p < 0.001) and trabecular microstructures(|R| = 0.46–0.78, p < 0.05). The scale parameter(i.e.,?) and signal-to-noise ratio(SNR) also yielded significant correlations with bone density and structural features. Multiple linear regressions showed that bone volume fraction(BV/TV) was the main predictor of the Nakagami parameters,and microstructure produced significantly independent contribution to the prediction of Nakagami distribution parameters,explaining an additional 10.2% of the variance at most. The in vitro study showed that statistical parameters derived with Nakagami model might be useful for cancellous bone characterization, and statistical analysis has potential for ultrasonic backscatter bone evaluation.

Amplitude modulation excitation for cancellous bone evaluation using a portable ultrasonic backscatter instrumentation

The ultrasonic backscatter(UB)has the advantage of non-invasively obtaining bone density and structure,expected to be an assessment tool for early diagnosis osteoporosis.All former UB measurements were based on exciting a short single-pulse and analyzing the ultrasonic signals backscattered in bone.This study aims to examine amplitude modulation(AM)ultrasonic excitation with UB measurements for predicting bone characteristics.The AM multiple lengths excitation and backscatter measurement(AM-UB)functions were integrated into a portable ultrasonic instrument for bone characterization.The apparent integrated backscatter coefficient in the AM excitation(AIB_(AM))was evaluated on the AM-UB instrumentation.The correlation coefficients of the AIB_(AM) estimating volume fraction(BV/TV),structure model index(SMI),and bone mineral density(BMD)were then analyzed.Significant correlations(|R|=0.82-0.93,p<0.05)were observed between the AIB_(AM),BV/TV,SMI,and BMD.By growing the AM excitation length,the AIB_(AM) values exhibit more stability both in 1.0-MHz and 3.5-MHz measurements.The recommendations in AM-UB measurement were that the avoided length(T1)should be lower than AM excitation length,and the analysis length(T2)should be enough long but not more than AM excitation length.The authors conducted an AM-UB measurement for cancellous bone characterization.Increasing the AM excitation length could substantially enhance AIB_(AM) values stability with varying analyzed signals.The study suggests the portable AM-UB instrument with the integration of real-time analytics software that might provide a potential tool for osteoporosis early screening.

Deep learning method for cell count from transmitted-light microscope

Automatic cell counting provides an effective tool for medical research and diagnosis.Currently,cell counting can be completed by transmitted-light microscope,however,it requires expert knowledge and the counting accuracy which is unsatisfied for overlapped cells.Further,the image-translation-based detection method has been proposed and the potential has been shown to accomplish cell counting from transmitted-light microscope,automatically and effectively.In this work,a new deep-learning(DL)-based two-stage detection method(cGAN-YOLO)is designed to further enhance the performance of cell counting,which is achieved by combining a DL-based fluorescent image translation model and a DL-based cell detection model.The various results show that cGAN-YOLO can effectively detect and count some different types of cells from the acquired transmitted-light microscope images.Compared with the previously reported YOLO-based one-stage detection method,high recognition accuracy(RA)is achieved by the cGAN-YOLO method,with an improvement of 29.80%.Furthermore,we can also observe that cGAN-YOLO obtains an improvement of 12.11%in RA compared with the previously reported image-translation-based detection method.In a word,cGAN-YOLO makes it possible to implement cell counting directly from the experimental acquired transmitted-light microscopy images with high flexibility and performance,which extends the applicability in clinical research.

The Protocol of Ultrasonic Backscatter Measurements of Musculoskeletal Properties

This study aims to introduce the protocol for ultrasonic backscatter measurements of musculoskeletal properties based on a novel ultrasonic backscatter bone diagnostic(UBBD)instrument.Dual-energy X-ray absorptiometry(DXA)can be adopted to measure bone mineral density(BMD)in the hip,spine,legs and the whole body.The muscle and fat mass in the legs and the whole body can be also calculated by DXA body composition analysis.Based on the proposed protocol for backscatter measurements by UBBD,ultrasonic backscatter signals can be measured in vivo,deriving three backscatter parameters[apparent integral backscatter(AIB),backscatter signal peak amplitude(BSPA)and the corresponding arrival time(BSPT)].AIB may provide important diagnostic information about bone properties.BSPA and BSPT may be important indicators of muscle and fat properties.The standardized backscatter measurement protocol of the UBBD instrument may have the potential to evaluate musculoskeletal characteristics,providing help for promoting the application of the backscatter technique in the clinical diagnosis of musculoskeletal disorders(MSDs),such as osteoporosis and muscular atrophy.

An Ultrasonic Backscatter Instrument for Cancellous Bone Evaluation in Neonates

Ultrasonic backscatter technique has shown promise as a noninvasive cancellous bone assessment tool. A novel ultrasonic backscatter bone diagnostic （UBBD） instrument and an in vivo application for neonatal bone evaluation are introduced in this study. The UBBD provides several advantages, including noninvasiveness, non- ionizing radiation, portability, and simplicity. In this study, the backscatter signal could be measured within 5 s using the UBBD. Ultrasonic backscatter measurements were performed on 467 neonates （268 males and 199 females） at the left calcaneus. The backscatter signal was measured at a central frequency of 3.5 MHz. The delay （-/-1） and duration （7-2） of the backscatter signal of interest （SOl） were varied, and the apparent integrated backscatter （AIB）, frequency slope of apparent backscatter （FSAB）, zero frequency intercept of apparent backscatter （FIAB）, and spectral centroid shift （SCS） were calculated. The results showed that the SOl selection had a direct influence on cancellous bone evaluation. The AIB and FIAB were positively correlated with the gestational age （｜R｜ up to 0.45, P 〈 0.001） when -/-1 was short （〈 8 μS）, while negative correlations （｜R｜ up to 0.56, P 〈 0.001） were commonly observed for T1 〉 10 IJS. Moderate positive correlations （IRI up to 0.45, P 〈 0.001） were observed for FSAB and SCS with gestational age when 71 was long （〉 10 μs）. The 7-2 mainly introduced fluctuations in the observed correlation coefficients. The moderate correlations observed with UBBD demonstrate the feasibility of using the backscatter signal to evaluate neonatal bone status. This study also proposes an explicit standard for in vivo SOl selection and neonatal cancellous bone assessment.

High-resolution bone microstructure imaging based on ultrasonic frequency-domain full-waveform inversion

The main challenge in bone ultrasound imaging is the large acoustic impedance contrast and sound velocity differences between the bone and surrounding soft tissue. It is difficult for conventional pulse-echo modalities to give accurate ultrasound images for irregular bone boundaries and microstructures using uniform sound velocity assumption rather than getting a prior knowledge of sound speed. To overcome these limitations, this paper proposed a frequency-domain fullwaveform inversion(FDFWI) algorithm for bone quantitative imaging utilizing ultrasonic computed tomography(USCT).The forward model was calculated in the frequency domain by solving the full-wave equation. The inverse problem was solved iteratively from low to high discrete frequency components via minimizing a cost function between the modeled and measured data. A quasi-Newton method called the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm(L-BFGS) was utilized in the optimization process. Then, bone images were obtained based on the estimation of the velocity and density. The performance of the proposed method was verified by numerical examples, from tubular bone phantom to single distal fibula model, and finally with a distal tibia-fibula pair model. Compared with the high-resolution peripheral quantitative computed tomography(HR-p QCT), the proposed FDFWI can also clearly and accurately presented the wavelength scaled pores and trabeculae in bone images. The results proved that the FDFWI is capable of reconstructing high-resolution ultrasound bone images with sub-millimeter resolution. The parametric bone images may have the potential for the diagnosis of bone disease.

Assessment of cortical bone fatigue using coded nonlinear ultrasound

Bone fatigue accumulation is a factor leading to bone fracture,which is a progressive process of microdamage deteriorating under long-term and repeated stress.Since the microdamage of the early stage in bone is difficult to be investigated by linear ultrasound,the second harmonic generation method in nonlinear ultrasound technique is employed in this paper,which is proved to be more sensitive to microdamage.To solve the deficiency that the second harmonic component is easily submerged by noise in traditional nonlinear measurement,a weighted chirp coded sinusoidal signal was applied as the ultrasonic excitation,while pulse inversion is implemented at the receiving side.The effectiveness of this combination to improve the signal-to-noise ratio has been demonstrated by in vitro experiment.Progressive fatigue loading experiments were conducted on the cortical bone plate in vitro for microdamage generation.There was a significant increase in the slope of the acoustic nonlinearity parameter with the propagation distance(increased by 8%and 24%respectively)when the bone specimen was at a progressive level of microdamage.These results indicate that the coded nonlinear ultrasonic method might have the potential in diagnosing bone fatigue.

Nonlinear inversion of ultrasonic guided waves for in vivo evaluation of cortical bone properties

Ultrasonic guided waves(UGWs),which propagate throughout the entire thickness of cortical bone,are attractive for the early diagnosis of osteoporosis.However,this is challenging due to the impact of soft tissue and the inherent difficulties related to multiparametric inversion of cortical bone quality factors,such as cortical thickness and bulk wave velocity.Therefore,in this research,a UGW-based multi-parameter inversion algorithm is developed to predict strength-related factors.In simulation,a free plate(cortical bone)and a bilayer plate(soft tissue and cortical bone)are used to validate the proposed method.The inversed cortical thickness(CTh),longitudinal velocity(V_(L))and transverse velocity(V_(T))are in accordance with the true values.Then four bovine cortical bone plates were used in in vitro experiments.Compared with the reference values,the relative errors for cortical thickness were 3.96%,0.83%,2.87%,and 4.25%,respectively.In the in vivo measurements,UGWs are collected from the tibias of 10 volunteers.The theoretical dispersion curves depicted by the estimated parameters(V_(T),V_(L),CTh)match well with the extracted experimental ones.In comparison with dual-energy x-ray absorptiometry,our results show that the estimated transverse velocity and cortical thickness are highly sensitive to osteoporosis.Therefore,these two parameters(CTh and V_(T))of long bones have potential to be used for diagnosis of bone status in clinical applications.

可编织、可穿戴的宽带聚合物超声换能器

新兴的物联网技术推动了可穿戴健康监测设备的快速发展.目前,医学超声技术在严重慢性疾病的长时间监测方面具有广阔的应用前景.然而,商用超声探头一般都是刚性的,需要手持,难以满足医疗可穿戴设备对柔性化、小型化和舒适性的要求.本文提出了一种可编织、可穿戴的聚合物超声换能器,该换能器由匹配层、背衬层和压电层组成.聚合物压电材料的带宽(93%)是压电陶瓷的7倍,并且可以承受超过10,000次的弯曲和扭曲变形.该传感器能监测颈动脉血液流速,心脏血液流速和心脏血管的血管厚度,并具有与商用探头相当的信噪比.它的宽带特性(3.68–10.08 MHz)使其能通过调整频率来监测不同的组织.可编织超声换能器可以制成纤维形式,并编织成透气织物,在不牺牲穿戴舒适性的情况下进行实时血管监测.

Screening COVID-19 from chest X-ray images by an optical diffractive neural network with the optimized F number

The COVID-19 pandemic continues to significantly impact people's lives worldwide, emphasizing the critical need for effective detection methods. Many existing deep learning-based approaches for COVID-19 detection offer high accuracy but demand substantial computing resources, time, and energy. In this study, we introduce an optical diffractive neural network(ODNN-COVID), which is characterized by low power consumption, efficient parallelization, and fast computing speed for COVID-19 detection. In addition, we explore how the physical parameters of ODNN-COVID affect its diagnostic performance. We identify the F number as a key parameter for evaluating the overall detection capabilities. Through an assessment of the connectivity of the diffractive network, we established an optimized range of F number, offering guidance for constructing optical diffractive neural networks. In the numerical simulations, a three-layer system achieves an impressive overall accuracy of 92.64% and 88.89% in binary-and threeclassification diagnostic tasks. For a single-layer system, the simulation accuracy of 84.17% and the experimental accuracy of 80.83% can be obtained with the same configuration for the binary-classification task, and the simulation accuracy is 80.19% and the experimental accuracy is 74.44% for the three-classification task. Both simulations and experiments validate that the proposed optical diffractive neural network serves as a passive optical processor for effective COVID-19 diagnosis, featuring low power consumption, high parallelization, and fast computing capabilities. Furthermore, ODNN-COVID exhibits versatility, making it adaptable to various image analysis and object classification tasks related to medical fields owing to its general architecture.

Three-dimensional ultrasound subwavelength arbitrary focusing with broadband sparse metalens

Ultrasound focusing in three-dimensional(3 D)space is of crucial and enduring significance in a variety of biomedical and industrial applications.Conventional ultrasound focusing based on active phase array or passive geometry of bulky size is unable to realize the 3 D arbitrary focusing with subwavelength resolution.Acoustic metamaterial of complex deep-subwavelength microstructure has facilitated the advanced airborne-sound-focusing but is inevitably not applicable for underwater ultrasound,restricted by the law between the multi-modes coupling/thermal viscosity and the feature size of the structure.Here,we aim to circumvent the restriction by increasing the feature size of the metamaterial while keeping the compact overall geometry,and realize the robust subwavelength ultrasound focusing with the sparse metalens of the wavelength-scale meta-atom.We theoretically propose and demonstrate numerically and experimentally the broadband arbitrary ultrasound focusing in 3 D space.The axial and off-axis ultrasound focusing with the subwavelength resolution(FWHM<0.58λ)are achieved by the spatially sparse and compact metalens within one-octave bandwidth.With advantages of 3 D freewheeling focusing,subwavelength resolution,spatial sparsity,geometric simplicity,and broadband,the sparse metalens would offer more initiatives to advanced researches in ultrasound focusing and empower applications such as precise biomedical imaging and therapy,nondestructive evaluation,integrated and multiplexed ultrasound devices.

光声骨检测研究进展

光声成像及检测技术兼具生物组织对光的选择吸收特性及超声波的穿透深度优势,可提供生物组织的宏观生理结构和微观分子层面的影像信息,在医学检测中有着巨大的应用潜力.其中,光声骨成像及检测技术是光声成像临床应用领域的重要分支.然而,骨组织是固液两相复杂介质(固相为矿化的骨小梁网络,液相为嵌入的骨髓),这种各向异性的非均匀结构使得基于光声技术的骨组织表征方法面临很大挑战.本文系统讨论了面向复杂骨组织的光声检测及成像机制,包括光声在骨组织中的产生及传播理论、光声谱分析方法、光声骨成像方法及临床应用研究.针对现有的技术研究现状,分析了光声骨成像及检测领域当前所面临的挑战,展望了未来的发展趋势.

Virtual Fluorescence Translation for Biological Tissue by Conditional Generative Adversarial Network

Fluorescence labeling and imaging provide an opportunity to observe the structure of biological tissues,playing a crucial role in the field of histopathology.However,when labeling and imaging biological tissues,there are still some challenges,e.g.,time-consuming tissue preparation steps,expensive reagents,and signal bias due to photobleaching.To overcome these limitations,we present a deep-learning-based method for fluorescence translation of tissue sections,which is achieved by conditional generative adversarial network(cGAN).Experimental results from mouse kidney tissues demonstrate that the proposed method can predict the other types of fluorescence images from one raw fluorescence image,and implement the virtual multi-label fluorescent staining by merging the generated different fluorescence images as well.Moreover,this proposed method can also effectively reduce the time-consuming and laborious preparation in imaging processes,and further saves the cost and time.

Fluo-Fluo translation based on deep learning

Fluorescence microscopy technology uses fluorescent dyes to provide highly specific visualization of cell components,which plays an important role in understanding the subcellular structure.However,fluorescence microscopy has some limitations such as the risk of non-specific cross labeling in multi-labeled fluorescent staining and limited number of fluo-rescence labels due to spectral overlap.This paper proposes a deep learning-based fluorescence to fluorescence[Flu0-Fluo]translation method,which uses a conditional generative adversarial network to predict a fluorescence image from another fluorescence image and further realizes the multi-label fluorescent staining.The cell types used include human motor neurons,human breast cancer cells,rat cortical neurons,and rat cardiomyocytes.The effectiveness of the method is verified by successfully generating virtual fluorescence images highly similar to the true fluorescence images.This study shows that a deep neural network can implement Fluo-Fluo translation and describe the localization relationship between subcellular structures labeled with different fluorescent markers.The proposed Fluo-Fluo method can avoid non-specific cross labeling in multi-label fluorescence staining and is free from spectral overlaps.In theory,an unlimited number of fluorescence images can be predicted from a single fluorescence image to characterize cells.

Feasibility study for bone health assessment based on photoacoustic imaging method

This study investigated the feasibility of photoacoustic(PA) imaging of bone and characterization of bone features. By conducting the experiments on bovine femoral heads ex vivo, the light and ultrasonic penetration in bones was studied, together with the depth of PA imaging and measurement in bones. Then, the possibility of three-dimensional(3 D) PA imaging of bones by raster scanning of the focusing transducer was studied. The micro-computerized tomography images of the bovine ribs with and without ethylenediaminetetraacetic acid(EDTA) treatment indicated that the 3 D PA images could present the changes of bone microstructure resulting from the EDTA treatment. By using PA spectral analysis, the bone samples with and without the treatment of EDTA solution can be distinguished, and the microstructures can be characterized. This study was based on the bovine bone whose size is comparable to human bones, suggesting that PA technology can be used as a novel bone diagnostic technique.