Search Results (119)

Coronary plaque vulnerability, more than luminal stenosis, drives acute coronary syndromes. Optical coherence tomography (OCT), intravascular ultrasound (IVUS), and coronary computed tomography angiography (CCTA) visualize plaque morphology in vivo, but manual interpretation is time-consuming and operator-dependent. We performed a narrative literature survey of artificial intelligence (AI) applications—focusing on machine learning (ML) architectures—for automated coronary plaque segmentation and risk characterization across OCT, IVUS, and CCTA. Recent ML models achieve expert-level lumen and plaque segmentation, reliably detecting features linked to vulnerability such as a lipid-rich necrotic core, calcification, positive remodelling, and a napkin-ring sign. Integrative radiomic and multimodal frameworks further improve prognostic stratification for major adverse cardiac events. Nonetheless, progress is constrained by small, single-centre datasets, heterogeneous validation metrics, and limited model interpretability. AI-enhanced plaque assessment offers rapid, reproducible, and comprehensive coronary imaging analysis. Future work should prioritize large multicentre repositories, explainable architectures, and prospective outcome-oriented validation to enable routine clinical adoption. Full article

Cardiac allograft vasculopathy (CAV) is a leading cause of allograft dysfunction and failure. CAV prevention, early detection, and management are essential to increasing allograft survival. In this comprehensive review, we discuss various invasive and non-invasive modalities that are being utilized for CAV detection. Invasive coronary angiography provides a visualization of vascular anatomy but is limited in detecting the microvasculature and diffuse and early structural changes. The addition of intracoronary assessment techniques, including intravascular ultrasound, optical coherence tomography, and coronary flow reserve assessment, offer(s) superior sensitivity in identifying CAV. Non-invasive imaging modalities, such as cardiac magnetic resonance imaging, computed tomography angiography, and positron emission tomography, provide complementary insights into CAV with myocardial perfusion and allograft function while reducing procedural risks. Our aim is to guide clinicians in selecting appropriate imaging strategies tailored to individual recipients, to improve detection, monitoring, and outcomes in CAV. Full article

In fiber Bragg grating (FBG) sensing demodulation systems, high-precision peak detection is a core requirement for demodulation algorithms. However, practical spectral signals are often susceptible to environmental noise interference, which leads to significant degradation in the accuracy of traditional demodulation methods. This study proposes a self-adaptive K-SVD (SAK-SVD) denoising algorithm based on adaptive window parameter optimization, establishing a closed-loop iterative feedback mechanism through dual iterations between dictionary learning and parameter adjustment. This approach achieves a synergistic enhancement of noise suppression and signal fidelity. First, a dictionary learning framework based on K-SVD is constructed for initial denoising, and the peak feature region is extracted by differentiating the denoised signals. By constructing statistics on the number of sign changes, an adaptive adjustment model for the window size is established. This model dynamically tunes the window parameters in dictionary learning for iterative denoising, establishing a closed-loop architecture that integrates denoising evaluation with parameter optimization. The performance of SAK-SVD is evaluated through three experimental scenarios, demonstrating that SAK-SVD overcomes the rigid parameter limitations of traditional K-SVD in FBG spectral processing, enhances denoising performance, and thereby improves wavelength demodulation accuracy. For denoising undistorted waveforms, the optimal mean absolute error (MAE) decreases to 0.300 pm, representing a 25% reduction compared to the next-best method. For distorted waveforms, the optimal MAE drops to 3.9 pm, achieving a 63.38% reduction compared to the next-best method. This study provides both theoretical and technical support for high-precision fiber-optic sensing under complex working conditions. Crucially, the SAK-SVD framework establishes a universal, adaptive denoising paradigm for fiber Bragg grating (FBG) sensing. This paradigm has direct applicability to Raman spectroscopy, industrial ultrasound-based non-destructive testing, and biomedical signal enhancement (e.g., ECG artefact removal), thereby advancing high-precision measurement capabilities across photonics and engineering domains. Full article

Optical Coherence Tomography (OCT) is a relatively new medical imaging device that provides high-resolution and real-time visualization of biological tissues. Initially designed for ophthalmology, OCT is now being applied in other types of pathologies, like cancer diagnosis. This review highlights its impact on disease diagnosis, biopsy guidance, and treatment monitoring. Despite its advantages, OCT has limitations, particularly in tissue penetration and differentiating between malignant and benign lesions. To overcome these challenges, the integration of nanoparticles has emerged as a transformative approach, which significantly enhances contrast and tumor vascularization at the molecular level. Gold and superparamagnetic iron oxide nanoparticles, for instance, have demonstrated great potential in increasing OCT’s diagnostic accuracy through enhanced optical scattering and targeted biomarker detection. Beyond these innovations, integrating OCT with multimodal imaging methods, including magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasound, offers a more comprehensive approach to disease assessment, particularly in oncology. Additionally, advances in artificial intelligence (AI) and biosensors have further expanded OCT’s capabilities, enabling real-time tumor characterization and optimizing surgical precision. However, despite these advancements, clinical adoption still faces several hurdles. Issues related to nanoparticle biocompatibility, regulatory approvals, and standardization need to be addressed. Moving forward, research should focus on refining nanoparticle technology, improving AI-driven image analysis, and ensuring broader accessibility to OCT-guided diagnostics. By tackling these challenges, OCT could become an essential tool in precision medicine, facilitating early disease detection, real-time monitoring, and personalized treatment for improved patient outcomes. Full article

Cancer remains a leading global cause of mortality, highlighting the critical need for effective early diagnosis. Despite advancements in treatment, early detection and imaging continue to pose significant challenges. Functionalized carbon nanotubes (CNTs) have emerged as promising nanomaterials due to their unique structural properties and versatile functionalization strategies. This review explores the role of both covalent (e.g., fluorination, hydrogenation, cycloadditions, aryldiazonium salt reduction, organometallic ion attachment, carboxylation, amidation, esterification, and metallic nanoparticle attachments) and non-covalent functionalization methods (e.g., surfactant coating, polymer wrapping, biomolecule attachment, and polymer encapsulation) in enhancing CNT biocompatibility and diagnostic efficiency. Functionalized CNTs are extensively applied in cancer detection through highly sensitive biosensors, including electrochemical, optical, and field-effect transistor-based systems, capable of detecting various cancer biomarkers with exceptional sensitivity. Additionally, they offer significant advantages in cancer imaging modalities such as fluorescence imaging, magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound imaging, improving contrast, resolution, and specificity. This review also discusses the challenges and future directions in the development of CNT-based diagnostic platforms, emphasizing the need for continued research to advance their clinical translation and integration into routine cancer diagnostics. Full article

The existence of bubble defects in ultra-low expansion quartz glass will affect the optical properties and mechanical strength of the material. The present paper proposes a novel defect characterization method based on ultrasonic nondestructive testing. The simulation model of bubble defect detection in ultra-low expansion quartz glass was established using numerical simulation technology, and experimental verification was carried out. The propagation mechanism of the ultrasound and its interaction with bubble defects were then analyzed. The results showed that the shape of the reflected wave was similar to that of the corresponding defect, and the scattering of the reflected wave was different due to the different curvature radius of the defect interface. The acoustic scattering characteristics of the circular defect were more obvious than those of the elliptical defect. Finally, an analysis of the interaction between different depth defects and different size defects and the ultrasound was conducted, leading to the conclusion that the relative amplitude of the defect echo corresponding to a 6 mm probe diameter shows a monotonic decreasing relationship with the defect depth, and there is also a monotonic corresponding relationship between the relative amplitude of the defect echo and the size of bubble defect. Therefore, it can be concluded that the relative amplitude of the defect echo can be used to characterize the size of the bubble defect. This study not only analyses the interaction between defects and ultrasound but also provides a quantitative characterization of defects using the proposed method. Full article

Background and Clinical Significance: Choroidal nevi are common benign growths originating from pigment cells in the fundus of the eye. They are typically up to 5 mm in diameter, asymptomatic, and incidentally discovered during routine ophthalmological examinations. Case Presentation: We present the case of a 48-year-old woman with presbyopic complaints and an incidental finding of a large, pigmented, slightly raised tumor in the fundus of the left eye. Examinations revealed normal visual acuity in both eyes and normal intraocular pressure. Ophthalmoscopy of the left eye identified a large, pigmented lesion measuring 11.55 mm in diameter, with drusen-like deposits along the superior nasal vascular arch. Fluorescein angiography showed atrophic changes in the retinal pigment epithelium without evidence of a pathological vascular network. Ultrasound revealed dimensions of 10.21 mm at the base and 0.57 mm prominence, with no changes observed during a one-year follow-up. Optical coherence tomography (OCT) did not detect any subretinal fluid. The right eye appeared normal. Based on these findings, a giant choroidal nevus in the left eye was suspected, and the clinical approach involved monitoring at 3- to 6-month intervals. Discussion: This case highlights the diagnostic challenges associated with a large, pigmented fundus lesion in a relatively young patient. Giant choroidal nevi, defined as lesions larger than 10 mm at the base, may clinically mimic malignant melanoma. However, features such as drusen and atrophic changes in the retinal pigment epithelium suggest a chronic process. Differentiating between giant choroidal nevi and malignant melanoma is essential due to differing therapeutic approaches. Since some choroidal nevi can undergo malignant transformation, close monitoring for signs of malignancy is crucial. Conclusions: The size of pigmented nevi is a significant risk factor for malignant transformation, underscoring the importance of long-term follow-up for affected patients. Full article

Intraluminal photoacoustic (PA) imaging has the potential for providing physiological and functional information in wide-ranging clinical applications. Along with endoluminal ultrasound transducers, these applications require compact light delivery devices which can deliver high-energy ns-pulsed laser to the target region. In this work, we describe the design, method of fabrication and characterization of a new compact, side-fire optical fiber that can deliver high-energy laser pulses for PA imaging. Side-fire illuminators were fabricated using UV laser ablation to create windows on the side of a 1.5 mm diameter single core, multi-mode optical fiber with a reflective silver coating and a beveled end. Devices with 10 mm, 20 mm, and 30 mm window lengths were fabricated and their beam profiles characterized. Elongated side-fire fibers with −6 dB beam size up to 30.79 mm × 5.5 mm were developed. A side-fire to total output ratio of up to 0.69 and a side fire efficiency of up to 40%, relative to a standard front-fire fiber, were achieved. We evaluated the effects of high-energy ns-pulsed light propagation on the fiber by coupling the fiber to 18 mJ or 100 MW/cm² (at 750 nm) beam from a Q-switched laser. The PA imaging with the fiber was demonstrated by detecting India ink targets embedded in chicken breast tissue over the full length of a 20 mm illumination window and over a 100° angle and by visualizing in vivo the rat ear vasculature. Full article

Non-contact laser ultrasonic detection technology provides an innovative solution for evaluating the internal conditions of lithium-ion batteries (LIBs), offering significant advantages in gas defect assessment and structural defect identification. This study proposes a method for evaluating internal gas defects in LIBs based on a non-contact laser ultrasonic system. The system uses a pulsed laser to generate ultrasonic waves, with a full-optical probe receiving the signals, enabling high-resolution imaging of the internal features of the battery. The study analyzes key ultrasonic characteristics under different laser parameters (energy, pulse width, and focal length) and their correlation with defective regions. Through both time-domain and frequency-domain analysis of the ultrasonic features, the results demonstrate that the signal amplitude attenuation characteristics of ultrasound in media with acoustic impedance mismatches can be used for precise detection and quantitative characterization of gas defect regions within the battery. This non-contact technology offers a promising method for real-time, non-destructive monitoring of the internal condition of lithium-ion batteries, significantly enhancing battery safety and reliability. Full article

Photoacoustic (PA) imaging combines optical contrast with ultrasound (US) detection, enabling high-resolution imaging of biological tissues with greater penetration depth than conventional optical techniques. Among its various implementations, photoacoustic microscopy (PAM) achieves micrometer-scale resolution by focusing laser excitation and detecting ultrasonic signals, allowing for the detailed visualization of microvascular structures and fine tissue morphology. Over the last decade, PAM imaging speed has significantly increased by adopting PA scanners that steer optical and acoustic waves. However, these scanners must be placed after focusing optics to co-align the waves on a spot, which creates bent focal lines along the scanning direction and limits the scanning range. To achieve wide-field imaging, various image mosaic algorithms have been applied, but these methods require multiple manual operations, which take more time than the imaging itself. In this study, we developed a wide-field, high-speed scanning acoustic/photoacoustic microscopy (SA/PAM) system equipped with a transparent ultrasound transducer and a moving magnet linear stage, which eliminates the need for complex mosaic algorithms. This system enables wide-field imaging up to 50 × 50 mm² while maintaining high lateral resolution, achieving an imaging speed of 50 Hz in a B-scan image. Through in vivo mouse US/PA imaging, the system demonstrated its capability to visualize blood vessels and organs across the whole body of small animals. These findings suggest that the SA/PAM system is a practical tool for biomedical research, allowing for efficient visualization of vascular networks and anatomical structures in various preclinical studies. Full article

Photoacoustic imaging (PAI) is an emerging modality that merges optical and ultrasound imaging to provide high-resolution and functional insights into biological tissues. This technique leverages the photoacoustic effect, where tissue absorbs pulsed laser light, generating acoustic waves that are captured to reconstruct images. While lasers have traditionally been the light source for PAI, their high cost and complexity drive interest towards alternative sources like light-emitting diodes (LEDs). This study evaluates the feasibility of using an avalanche oscillator to drive high-power LEDs in a basic photoacoustic imaging system. An avalanche oscillator, utilizing semiconductor avalanche breakdown to produce high-voltage pulses, powers LEDs to generate short, high-intensity light pulses. The system incorporates an LED array, an ultrasonic transducer, and an amplifier for signal detection. Key findings include the successful generation of short light pulses with sufficient intensity to excite materials and the system’s capability to produce detectable photoacoustic signals in both air and water environments. While LEDs demonstrate cost-effectiveness and portability advantages, challenges such as lower power and broader spectral bandwidth compared to lasers are noted. The results affirm that LED-based photoacoustic systems, though currently less advanced than laser-based systems, present a promising direction for affordable and portable imaging technologies. Full article

Breast cancer remains a leading cause of cancer-related deaths among women, emphasizing the critical need for early detection and monitoring techniques. Conventional imaging modalities such as mammography, MRI, and ultrasound have face sensitivity, specificity, cost, and patient comfort limitations. This study introduces a handheld Near-Infrared Diffuse Optical Tomography (NIR DOT) probe for breast cancer imaging. The NIRscan probe utilizes multi-wavelength light-emitting diodes (LEDs) and a linear charge-coupled device (CCD) sensor to acquire real-time optical data, reconstructing cross-sectional images of breast tissue based on scattering and absorption coefficients. With wavelengths optimized for the differential optical properties of tissue components, the probe enables functional imaging, distinguishing between healthy and malignant tissues. Clinical evaluations have demonstrated its potential for precise tumor localization and monitoring therapeutic responses, achieving a sensitivity of 94.7% and specificity of 84.2%. By incorporating machine learning algorithms and a modified diffusion equation (MDE), the system enhances the accuracy and speed of image reconstruction, supporting rapid, non-invasive diagnostics. This development represents a significant step forward in portable, cost-effective solutions for breast cancer detection, with potential applications in low-resource settings and diverse clinical environments. Full article

In areas where there is high humidity and freezing rain, there is a tendency of blade icing on wind turbines. It results in energy dissipation and mechanical abrasion and also creates a safety concern due to the risk of having falling ice. Real-time online detection of icing is crucial in the enhancement of power generation efficiency and in the safety of wind turbines. The current methods of icing detection that use ultrasound, optics, vibration, and electromagnetics are already studied. But these methods have their drawbacks, including small detection ranges, low accuracy, large size, and challenges in distributed installation, making it hard to capture the real-time dynamics of the icing and de-icing processes on the wind turbine blades. To this end, this paper presents a new blade surface icing detection technique using microstrip lines. This approach uses the impact of icing state and thickness on the effective dielectric constant of the microstrip line surface. This paper presents the analysis of time-domain features of microwave signals, which facilitates the identification of both the icing state and the corresponding thickness. Simulation and experimental measurement of linear and S-shaped microstrip sensors are used in this research in order to compare the response of the sensors to the variation in the thickness of the icing layer. It is seen that for icing thickness ranging from 0 mm to 6 mm, the imaginary part of the S21 parameter of the S-shaped microstrip line has a more significant change than that of the linear microstrip line. The above experiments also confirm that the phase shift value of the S-shaped microstrip line is always higher than that of the linear microstrip line for the same variation of icing thickness, which proves that the S-shaped microstrip line is more sensitive than the linear one. Also, it was possible to establish the relationship between the phase shift values and icing thickness, which makes it possible to predict the icing thickness. The developed microwave microstrip detection technology is intended for usage in the wind turbine blade icing and similar surface detection areas. This method saves the size and thickness of icing sensors, which makes it possible to conduct measurements at various points. This is especially beneficial for usage in wind turbine blades and can be further applied in aerospace, automotive, and construction, especially the bridges. Full article

MEMS acoustic sensors are a type of physical quantity sensor based on MEMS manufacturing technology for detecting sound waves. They utilize various sensitive structures such as thin films, cantilever beams, or cilia to collect acoustic energy, and use certain transduction principles to read out the generated strain, thereby obtaining the targeted acoustic signal’s information, such as its intensity, direction, and distribution. Due to their advantages in miniaturization, low power consumption, high precision, high consistency, high repeatability, high reliability, and ease of integration, MEMS acoustic sensors are widely applied in many areas, such as consumer electronics, industrial perception, military equipment, and health monitoring. Through different sensing mechanisms, they can be used to detect sound energy density, acoustic pressure distribution, and sound wave direction. This article focuses on piezoelectric, piezoresistive, capacitive, and optical MEMS acoustic sensors, showcasing their development in recent years, as well as innovations in their structure, process, and design methods. Then, this review compares the performance of devices with similar working principles. MEMS acoustic sensors have been increasingly widely applied in various fields, including traditional advantage areas such as microphones, stethoscopes, hydrophones, and ultrasound imaging, and cutting-edge fields such as biomedical wearable and implantable devices. Full article

Acute coronary syndrome (ACS) represents the most severe manifestation of coronary artery disease. Intravascular imaging, both intravascular ultrasound (IVUS) and optical coherence tomography (OCT), have played crucial roles for the impressive reduction in mortality of ACS. Intravascular imaging is useful for the detection of atherosclerotic mechanism (plaque rupture, calcified nodules, or plaque erosions) and for the evaluation of nonatherosclerotic and nonobstructive types of ACS. In addition, IVUS and OCT play a crucial role in the optimization of the PCI. The aim of the current review is to present the role of intravascular imaging in identifying the mechanisms of ACS and its prognostic role in future events, to review the current guidelines suggesting intravascular imaging use in ACS, to summarize its role in PCI in patients with ACS, and to compare IVUS and OCT. Full article