Epileptic brain network mechanisms and neuroimaging techniques for the brain network

Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

Advances in the application of auxiliary imaging techniques in parathyroid diseases

Hypoparathyroidism is one of the main complications after total thyroidectomy,severely affecting patients’quality of life.How to effectively protect parathyroid function after surgery and reduce the incidence of hypoparathyroidism has always been a key research area in thyroid surgery.Therefore,precise localization of parathyroid glands during surgery,effective imaging,and accurate surgical resection have become hot topics of concern for thyroid surgeons.In response to this clinical phenomenon,this study compared several different imaging methods for parathyroid surgery,including nanocarbon,indocyanine green,near-infrared imaging techniques,and technetium-99m methoxyisobutylisonitrile combined with gamma probe imaging technology.The advantages and disadvantages of each method were analyzed,providing scientific recommendations for future parathyroid imaging.In recent years,some related basic and clinical research has also been conducted in thyroid surgery.This article reviewed relevant literature and provided an overview of the practical application progress of various imaging techniques in parathyroid surgery.

Randomization Strategies in Image Steganography Techniques:A Review

Image steganography is one of the prominent technologies in data hiding standards.Steganographic system performance mostly depends on the embedding strategy.Its goal is to embed strictly confidential information into images without causing perceptible changes in the original image.The randomization strategies in data embedding techniques may utilize random domains,pixels,or region-of-interest for concealing secrets into a cover image,preventing information from being discovered by an attacker.The implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility,but it is challenging.A systematic approach is used with a standard methodology to carry out this study.This review concentrates on the critical examination of several embedding strategies,incorporating experimental results with state-of-the-art methods emphasizing the robustness,security,payload capacity,and visual quality metrics of the stego images.The fundamental ideas of steganography are presented in this work,along with a unique viewpoint that sets it apart from previous works by highlighting research gaps,important problems,and difficulties.Additionally,it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography.

Research on Image Recognition Using Deep Learning Techniques

This study delves into the applications,challenges,and future directions of deep learning techniques in the field of image recognition.Deep learning,particularly Convolutional Neural Networks(CNNs),Recurrent Neural Networks(RNNs),and Generative Adversarial Networks(GANs),has become key to enhancing the precision and efficiency of image recognition.These models are capable of processing complex visual data,facilitating efficient feature extraction and image classification.However,acquiring and annotating high-quality,diverse datasets,addressing imbalances in datasets,and model training and optimization remain significant challenges in this domain.The paper proposes strategies for improving data augmentation,optimizing model architectures,and employing automated model optimization tools to address these challenges,while also emphasizing the importance of considering ethical issues in technological advancements.As technology continues to evolve,the application of deep learning in image recognition will further demonstrate its potent capability to solve complex problems,driving society towards more inclusive and diverse development.

Non-invasive evaluation of liver steatosis with imaging modalities:New techniques and applications

In the world,nonalcoholic fatty liver disease(NAFLD)accounts for majority of diffuse hepatic diseases.Notably,substantial liver fat accumulation can trigger and accelerate hepatic fibrosis,thus contributing to disease progression.Moreover,the presence of NAFLD not only puts adverse influences for liver but is also associated with an increased risk of type 2 diabetes and cardiovascular diseases.Therefore,early detection and quantified measurement of hepatic fat content are of great importance.Liver biopsy is currently the most accurate method for the evaluation of hepatic steatosis.However,liver biopsy has several limitations,namely,its invasiveness,sampling error,high cost and moderate intraobserver and interobserver reproducibility.Recently,various quantitative imaging techniques have been developed for the diagnosis and quantified measurement of hepatic fat content,including ultrasound-or magnetic resonancebased methods.These quantitative imaging techniques can provide objective continuous metrics associated with liver fat content and be recorded for comparison when patients receive check-ups to evaluate changes in liver fat content,which is useful for longitudinal follow-up.In this review,we introduce several imaging techniques and describe their diagnostic performance for the diagnosis and quantified measurement of hepatic fat content.

Super-resolution Imaging of Telescopic Systems based on Optical-neural Network Joint Optimization

Optical telescopes are an important tool for acquiring optical information about distant objects,and resolution is an important indicator that measures the ability to observe object details.However,due to the effects of system aberration,atmospheric seeing,and other factors,the observed image of ground-based telescopes is often degraded,resulting in reduced resolution.This paper proposes an optical-neural network joint optimization method to improve the resolution of the observed image by co-optimizing the point-spread function(PSF)of the telescopic system and the image super-resolution(SR)network.To improve the speed of image reconstruction,we designed a generative adversarial net(LCR-GAN)with light parameters,which is much faster than the latest unsupervised networks.To reconstruct the PSF trained by the network in the optical path,a phase mask is introduced.It improves the image reconstruction effect of LCR-GAN by reconstructing the PSF that best matches the network.The results of simulation and verification experiments show that compared with the pure deep learning method,the SR image reconstructed by this method is rich in detail and it is easier to distinguish stars or stripes.

E-Cervix imaging displaying cervical elasticity characteristics of healthy adult nulliparous women at different age groups and different menstrual cycle stages

Objective To observe the cervical elasticity of healthy adult nulliparous women at different age groups and different stages of menstrual cycle with E-Cervix imaging technology.Methods A total of 218 healthy adult nulliparous women who underwent transvaginal ultrasound examination for routine physical examination were retrospectively enrolled,including 103 in follicular phase,78 in ovulation phase and 37 in luteal phase.Cervical canal length(CL)and E-Cervix elasticity parameters were compared among different age groups and different stages of menstrual cycle,including elasticity contrast index(ECI),hardness ratio(HR),cervical internal and external orifice strain values(IOS and EOS)and IOS/EOS ratio.Results No significant difference of CL nor cervical elasticity parameters was detected among healthy adult nulliparous women at different age groups(all P>0.05).There were significant differences of ECI,HR and IOS among different menstrual cycle stages(all P<0.05),among which women in follicular phase had higher ECI and IOS but lower HR than those in luteal phase(all P<0.05).Conclusion No significant difference of cervical elasticity existed among healthy adult nulliparous women at different age groups.Meanwhile,cervical elasticity of healthy adult nulliparous women changed during menstrual cycle,in follicular phase had higher ECI and IOS but lower HR than in luteal phase.

A Systematic Review of Computer Vision Techniques for Quality Control in End-of-Line Visual Inspection of Antenna Parts

The rapid evolution of wireless communication technologies has underscored the critical role of antennas in ensuring seamless connectivity.Antenna defects,ranging from manufacturing imperfections to environmental wear,pose significant challenges to the reliability and performance of communication systems.This review paper navigates the landscape of antenna defect detection,emphasizing the need for a nuanced understanding of various defect types and the associated challenges in visual detection.This review paper serves as a valuable resource for researchers,engineers,and practitioners engaged in the design and maintenance of communication systems.The insights presented here pave the way for enhanced reliability in antenna systems through targeted defect detection measures.In this study,a comprehensive literature analysis on computer vision algorithms that are employed in end-of-line visual inspection of antenna parts is presented.The PRISMA principles will be followed throughout the review,and its goals are to provide a summary of recent research,identify relevant computer vision techniques,and evaluate how effective these techniques are in discovering defects during inspections.It contains articles from scholarly journals as well as papers presented at conferences up until June 2023.This research utilized search phrases that were relevant,and papers were chosen based on whether or not they met certain inclusion and exclusion criteria.In this study,several different computer vision approaches,such as feature extraction and defect classification,are broken down and analyzed.Additionally,their applicability and performance are discussed.The review highlights the significance of utilizing a wide variety of datasets and measurement criteria.The findings of this study add to the existing body of knowledge and point researchers in the direction of promising new areas of investigation,such as real-time inspection systems and multispectral imaging.This review,on its whole,offers a complete study of computer vision approaches for quality control in antenna parts.It does so by providing helpful insights and drawing attention to areas that require additional exploration.

Imaging-based prediction of hepatocellular carcinoma recurrence after microwave ablation as bridge therapy: A glimpse into the future

Liver transplantation(LT)remains the treatment of choice for early-stage hepato-cellular carcinoma(HCC)and offers the best long-term oncological outcomes.However,the increasing waiting list for LT has led to a significant dropout rate as patients experience tumor progression beyond the Milan criteria.Currently,locoregional therapies,such as microwave ablation(MWA),have emerged as promising bridge treatments for patients awaiting LT.These therapies have shown promising results in preventing tumor progression,thus reducing the dropout rate of LT candidates.Despite the efficacy of MWA in treating HCC,tumoral recurrence after ablation remains a major challenge and significantly impacts the prognosis of HCC patients.Therefore,accurately diagnosing tumoral recurrence post-ablation is crucial.Recent studies have developed novel imaging features based on magnetic resonance imaging of HCC,which could provide essential information for predicting early tumoral recurrence after MWA.These advancements could address this unresolved challenge,improving the clinical outcomes of patients on the LT waiting list.This article explored the current landscape of MWA as a bridge therapy for HCC within the Milan criteria,high-lighting the emerging role of novel imaging-based features aimed at improving the prediction of tumor recurrence after MWA.

Recent advances in optical techniques for dynamically probing cellular mechanobiology

Cellular mechanotransduction characterized by the transformation of mechanical stimuli into biochemical signals,represents a pivotal and complex process underpinning a multitude of cellular functionalities.This process is integral to diverse biological phenomena,including embryonic development,cell migration,tissue regeneration,and disease pathology,particularly in the context of cancer metastasis and cardiovascular diseases.Despite the profound biological and clinical significance of mechanotransduction,our understanding of this complex process remains incomplete.The recent development of advanced optical techniques enables in-situ force measurement and subcellular manipulation from the outer cell membrane to the organelles inside a cell.In this review,we delved into the current state-of-the-art techniques utilized to probe cellular mechanobiology,their principles,applications,and limitations.We mainly examined optical methodologies to quantitatively measure the mechanical properties of cells during intracellular transport,cell adhesion,and migration.We provided an introductory overview of various conventional and optical-based techniques for probing cellular mechanics.These techniques have provided into the dynamics of mechanobiology,their potential to unravel mechanistic intricacies and implications for therapeutic intervention.

Benign gallbladder diseases:Imaging techniques and tips for differentiating with malignant gallbladder diseases

Benign gallbladder diseases usually present with intraluminal lesions and localized or diffuse wall thickening.Intraluminal lesions of the gallbladder include gallstones,cholesterol polyps,adenomas,or sludge and polypoid type of gallbladder cancer must subsequently be excluded.Polyp size,stalk width,and enhancement intensity on contrast-enhanced ultrasound and degree of diffusion restriction may help differentiate cholesterol polyps and adenomas from gallbladder cancer.Localized gallbladder wall thickening is largely due to segmental or focal gallbladder adenomyomatosis,although infiltrative cancer may present similarly.Identification of Rokitansky-Aschoff sinuses is pivotal in diagnosing adenomyomatosis.The layered pattern,degree of enhancement,and integrity of the wall are imaging clues that help discriminate innocuous thickening from gallbladder cancer.High-resolution ultrasound is especially useful for analyzing the layering of gallbladder wall.A diffusely thickened wall is frequently seen in inflammatory processes of the gallbladder.Nevertheless,it is important to check for coexistent cancer in instances of acute cholecystitis.Ultrasound used alone is limited in evaluating complicated cholecystitis and often requires complementary computed tomography.In chronic cholecystitis,preservation of a two-layered wall and weak wall enhancement are diagnostic clues for excluding malignancy.Magnetic resonance imaging in conjunction with diffusion-weighted imaging helps to differentiate xathogranulomatous cholecystitis from gallbladder cancer by identifying the presence of fat and degree of diffusion restriction.Such distinctions require a familiarity with typical imaging features of various gallbladder diseases and an understanding of the roles that assorted imaging modalities play in gallbladder evaluations.

Imaging of the small bowel in Crohn's disease: A review of old and new techniques

The investigation of small bowel morphology is often mandatory in many patients with Crohn's disease. Traditional radiological techniques (small bowel enteroclysis and small bowel follow-through) have long been the only suitable methods for this purpose. In recent years, several alternative imaging techniques have been proposed. To review the most recent advances in imaging studies of the small bowel, with particular reference to their possible application in Crohn's disease, we conducted a complete review of the most important studies in which traditional and newer imaging methods were performed and compared in patients with Crohn's disease. Several radiological and endoscopic techniques are now available for the study of the small bowel; each of them is characterized by a distinct profile of favourable and unfavourable features. In some cases, they may also be used as complementary rather than alternative techniques. In everyday practice, the choice of the technique to be used stands upon its availability and a careful evaluation of diagnostic accuracy, clinical usefulness, safety and cost. The recent development ofinnovative imaging techniques has opened a new and exciting area in the exploration of the small bowel in Crohn's disease patients.

THEORY OF THE EEG CORTICAL IMAGING TECHNIQUES

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Recent advances in imaging techniques of renal masses

Multiphasic multidetector computed tomography(CT)forms the mainstay for the characterization of renal masses whereas magnetic resonance imaging(MRI)acts as a problem-solving tool in some cases.However,a few of the renal masses remain indeterminate even after evaluation by conventional imaging methods.To overcome the deficiency in current imaging techniques,advanced imaging methods have been devised and are being tested.This review will cover the role of contrast-enhanced ultrasonography,shear wave elastography,dual-energy CT,perfusion CT,MR perfusion,diffusion-weighted MRI,blood oxygen leveldependent MRI,MR spectroscopy,positron emission tomography(PET)/prostate-specific membrane antigen-PET in the characterization of renal masses.

Magnetic resonance imaging-based deep learning model to predict multiple firings in double-stapled colorectal anastomosis

BACKGROUND Multiple linear stapler firings during double stapling technique(DST)after laparoscopic low anterior resection(LAR)are associated with an increased risk of anastomotic leakage(AL).However,it is difficult to predict preoperatively the need for multiple linear stapler cartridges during DST anastomosis.AIM To develop a deep learning model to predict multiple firings during DST anastomosis based on pelvic magnetic resonance imaging(MRI).METHODS We collected 9476 MR images from 328 mid-low rectal cancer patients undergoing LAR with DST anastomosis,which were randomly divided into a training set(n=260)and testing set(n=68).Binary logistic regression was adopted to create a clinical model using six factors.The sequence of fast spin-echo T2-weighted MRI of the entire pelvis was segmented and analyzed.Pure-image and clinical-image integrated deep learning models were constructed using the mask region-based convolutional neural network segmentation tool and three-dimensional convolutional networks.Sensitivity,specificity,accuracy,positive predictive value(PPV),and area under the receiver operating characteristic curve(AUC)was calculated for each model.RESULTS The prevalence of≥3 linear stapler cartridges was 17.7%(58/328).The prevalence of AL was statistically significantly higher in patients with≥3 cartridges compared to those with≤2 cartridges(25.0%vs 11.8%,P=0.018).Preoperative carcinoembryonic antigen level>5 ng/mL(OR=2.11,95%CI 1.08-4.12,P=0.028)and tumor size≥5 cm(OR=3.57,95%CI 1.61-7.89,P=0.002)were recognized as independent risk factors for use of≥3 linear stapler cartridges.Diagnostic performance was better with the integrated model(accuracy=94.1%,PPV=87.5%,and AUC=0.88)compared with the clinical model(accuracy=86.7%,PPV=38.9%,and AUC=0.72)and the image model(accuracy=91.2%,PPV=83.3%,and AUC=0.81).CONCLUSION MRI-based deep learning model can predict the use of≥3 linear stapler cartridges during DST anastomosis in laparoscopic LAR surgery.This model might help determine the best anastomosis strategy by avoiding DST when there is a high probability of the need for≥3 linear stapler cartridges.

Comparison of four techniques for estimating temporal change of seismic velocity with passive image interferometry

Passive image interferometry （PII） is becoming a powerful tool for detecting the temporal variations in the Earth＇s structure, which applies coda wave interferometry to the waveforrns from the cross-correlation of seismic ambient noise. There are four techniques for estimating temporal change of seismic velocity with PII： moving-window cross-correlation technique （MWCCT）, moving-window cross-spectrum technique （MWCST）, stretching technique （ST） and moving-window stretching technique （MWST）. In this paper, we use the continuous seismic records from a typical station pair near the Wenchuan Ms8.0 earthquake fault zone and generate three sets of waveforms by stacking cross-correlation function of ambient noise with different numbers of days, and then apply four techniques to processing the three sets of waveforms and compare their results. Our results indicate that the techniques based on moving-window （MWCCT, MWCST and MWST） are superior in detecting the change of seismic velocity, and the MWCST can give a better estimate of velocity change than the other moving-window techniques due to measurement error. We also investigate the clock errors and their influences on measuring velocity change. We find that when the clock errors are not very large, they have limited impact on the estimate of the velocity change with the moving-window techniques.

The State-of-the-Art Review on Applications of Intrusive Sensing,Image Processing Techniques,and Machine Learning Methods in Pavement Monitoring and Analysis

In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.

Principle of subtraction ghost imaging in scattering medium

Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost imaging.The disturbance is usually eliminated by the method of pre-compensation.We deduce the intensity fluctuation correlation function of the ghost imaging with the disturbance of the scattering medium,which proves that the ghost image consists of two correlated results:the image of scattering medium and the target object.The effect of the scattering medium can be eliminated by subtracting the correlated result between the light field after the scattering medium and the reference light from ghost image,which verifies the theoretical results.Our research may provide a new idea of ghost imaging in harsh environment.

Preprocedure ultrasound imaging combined with palpation technique in epidural labor analgesia

BACKGROUND For parturients with paroxysmal uterine contraction pain,rapid analgesia is needed.We used preprocedure ultrasound imaging combined with the palpation technique in epidural analgesia for labor,and evaluated the usefulness of this technique in epidural labor analgesia.AIM To evaluate the usefulness of preprocedure ultrasound imaging in epidural analgesia for labor.METHODS In this prospective randomized observational study,72 parturients were assigned to two groups(combined or palpation group).The target interspace of all parturients was first identified by the palpation technique.Then in the combined group,preprocedure ultrasound imaging was used before epidural puncture.In the palpation group,only the traditional anatomical landmarks technique(palpation technique)was performed.The primary outcome was total duration of the epidural procedure(for the ultrasound group,the duration of the preprocedure ultrasound imaging was included).The secondary outcomes were the number of skin punctures,the success rate at first needle pass,the number of needle passes,the depth from the skin to epidural space,and the complications of the procedure.RESULTS Total duration of the epidural procedure was similar between the two groups(406.5±92.15 s in the combined group and 380.03±128.2 s in the palpation group;P=0.318).A significant improvement was demonstrated for epidural puncture and catheterization in the combined group.The number of needle passes was 1.14 in the combined group and 1.72 in the palpation group(P=0.001).The number of skin puncture sites was 1.20 in the combined group and 1.25 in the palpation group(P=0.398).The success rate at first needle pass was 88.89%in the combined group and 66.67%in the palpation group(P=0.045).CONCLUSION This study demonstrated that the total duration of epidural procedures with preprocedure ultrasound imaging combined with the palpation technique was not longer than the traditional anatomical landmarks technique,which were performed by six experienced anesthesiologists in parturients with normal weights undergoing labor analgesia.