Image Research Articles

Classification of Pseudopapilledema and Papilledema Using Decision Tree and Hu Moments

Pseudopapilledema, characterized by an anomalous elevation of the optic disc without retinal nerve fiber layer edema, often mimics the presentation of true papilledema caused by increased intracranial pressure. Accurate differentiation between these conditions is critical to avoid unnecessary invasive procedures. This study employs a Decision Tree classifier to classify optic disc images into three categories: normal, papilledema, and pseudopapilledema. The dataset, obtained from Kaggle, consists of imbalanced images segmented using the Canny edge detection method and features extracted using Hu Moments. The dataset was divided into 80% training and 20% testing sets. Performance was evaluated using 5-fold cross-validation, yielding an average accuracy of 53.61%, precision of 55.20%, recall of 54.12%, and F1-score of 55.17%. The study provides a comprehensive analysis of the classifier's performance, including visualizations such as segmentation results, scatter plots of Hu Moments, and confusion matrices. The results indicate that while the Decision Tree classifier demonstrates moderate effectiveness, there is significant room for improvement. The research highlights the potential of machine learning models in medical diagnostics but also underscores the need for more robust algorithms and diverse datasets. Future work should focus on incorporating more complex models and expanding the dataset to enhance diagnostic accuracy. These findings contribute to the field of medical image analysis and propose a non-invasive diagnostic tool that, when integrated with clinical expertise, could improve patient outcomes and reduce unnecessary procedures

Research progress on aero-optical effects of hypersonic optical window with film cooling

AbstractIn recent years, the demand for optical imaging and detection in hypersonic aircraft has been on the rise. The high-temperature and high-pressure compressed flow field near airborne optoelectronic devices creates significant interference with light transmission, known as hypersonic aero-optical effects. This effect has emerged as a key technological challenge, limiting hypersonic optical imaging and detection capabilities. This article focuses on introducing the thermal effects and optical transmission effects of hypersonic aero-optical effects, as along with corresponding suppression techniques. In addition, this article critically reviews and succinctly summarizes the advancements made in hypersonic aero-optical effects testing technology, while also delineating avenues for future research needs in this field. In conclusion, there is an urgent call for further exploration into the study of aero-optical effects under conditions characterized by high Mach, high enthalpy, and high Reynolds number in the future.

Indoor lighting environment space design simulation system based on optical imaging and intelligent manufacturing

Indoor lighting environment space design simulation system based on optical imaging and intelligent manufacturing

Modular Design and Scaffold‐Synthesis of Multi‐Functional Fluorophores for Targeted Cellular Imaging and Pyroptosis

AbstractFluorophores are essential tools for optical imaging and biomedical research. Their synthetic modification to incorporate new functions, however, remains a challenging task. Conventional strategies rely on linear synthesis in which a parent framework is gradually extended. We here designed and synthesized a versatile library of multi‐functional fluorophores via a scaffold‐based Ugi four‐component reaction (U‐4CR). The adaptability of the scaffold is achieved through modification of starting materials. This allows to use a small range of starting materials for the creation of fluorogenic probes that can detect reactive‐oxygen species and where the localization into subcellular organelles or membranes can be controlled. We present reaction yields ranging from 60 % to 90 % and discovered that some compounds can even function as imaging and therapeutic agents via Fenton chemistry inducing pyroptosis in living cancer cells. Our study underlines the potential of scaffold‐based synthesis for versatile creation of functional fluorophores and their applications.

Real-time analysis of liquid jet sample delivery stability for an X-ray free-electron laser using machine vision

Automated evaluation of optical microscopy images of liquid jets, commonly used for sample delivery at X-ray free-electron lasers (XFELs), enables real-time tracking of the jet position and liquid jet hit rates, defined here as the proportion of XFEL pulses intersecting with the liquid jet. This method utilizes machine vision for preprocessing, feature extraction, segmentation and jet detection as well as tracking to extract key physical characteristics (such as the jet angle) from optical microscopy images captured during experiments. To determine the effectiveness of these tools in monitoring jet stability and enhancing sample delivery efficiency, we conducted XFEL experiments with various sample compositions (pure water, buffer and buffer with crystals), nozzle designs and jetting conditions. We integrated our real-time analysis algorithm into the Karabo control system at the European XFEL. The results indicate that the algorithm performs well in monitoring the jet angle and provides a quantitative characterization of liquid jet stability through optical image analysis conducted during experiments.

Anti-VEGF treatment outcome prediction based on optical coherence tomography images in neovascular age-related macular degeneration using a deep neural network.

Age-related macular degeneration (AMD) is a major cause of blindness in developed countries, and the number of affected patients is increasing worldwide. Intravitreal injections of anti-vascular endothelial growth factor (VEGF) are the standard therapy for neovascular AMD (nAMD), and optical coherence tomography (OCT) is a crucial tool for evaluating the anatomical condition of the macula. However, OCT has limitations in accurately predicting the degree of functional and morphological improvement following intravitreal injections. Artificial intelligence (AI) has been proposed as a tool for predicting the treatment response of nAMD based on OCT biomarkers. Our study focuses on the development and assessment of an AI model utilizing the DenseNet201 algorithm. The model aims to predict anatomical improvement based on OCT images before, and during anti-VEGF therapy. The training process involves two scenarios: (1) using only preinjection OCT images and (2) utilizing both OCT images before and during anti-VEGF therapy for model training. The outcomes of our investigation, involving 2068 images from a cohort of 517 Korean patients diagnosed with nAMD, indicate that the AI model we introduced surpassed the predictive performance of ophthalmologists. The model exhibited a sensitivity of 0.915, specificity of 0.426, and accuracy of 0.820. Notably, its predictive capabilities were further enhanced with the inclusion of additional OCT images taken after the first and second injections during the loading phase. The treatment prediction performance of the model was the highest when using all input modalities (before injection, and after the first and second injections) and concatenation-based fusion layers. This study highlights the potential of AI in assisting individualized and tailored nAMD treatment.

Design, manufacturing, and multi-modal imaging of stereolithography 3D printed flexible intracranial aneurysm phantoms.

Physical vascular phantoms are instrumental in studying intracranial aneurysms and testing relevant imaging tools and training systems to provide improved clinical care. Current vascular phantom production methods have major limitations in capturing the biophysical and morphological characteristics of intracranial aneurysms with good fidelity and multi-modal imaging capacity. With stereolithography (SLA) 3D printing technology becoming more accessible, newer flexible and transparent printing materials with higher precision controls open the door for improving the efficiency and quality of producing anthropomorphic vascular phantoms but have rarely been explored for the application. This technical note intends to report the feasibility of using SLA 3D printing technology to manufacture flexible intracranial aneurysm phantoms with similar scales to the real anatomy, as well as their capacity for multi-modal flow imaging and analysis, including ultrasound flow imaging, high-speed filming, and particle image velocimetry analysis. We designed and 3D-printed two intracranial aneurysm phantoms with an SLA 3D printer using Formlabs Elastic 50A resin. By using a micropump to introduce cyclical flows in the phantoms, we first employed conventional Doppler and vector flow ultrasonography to observe and measure different fluidic properties. Then, a high-speed camera was used to record particles flowing within the phantom, and we further conducted a particle image velocimetry analysis, including the distribution of mean 2D velocity vectors, average velocity magnitudes, and the mean vorticity fields in the phantom for the high-speed imaging data. We successfully 3D-printed flexible intracranial aneurysm phantoms with similar dimensions to the real anatomy. Additionally, we validated the phantoms' ability to allow visualization, measurement, and analysis of flow dynamics based on both real-time ultrasound and optical imaging. Our proof-of-concept study illustrates that SLA 3D printing using commercial elastic resins can significantly contribute towards facilitating the fabrication of flexible intracranial aneurysms phantoms for training, research, and preoperative planning.

Light-Emitting Coordination Polymers: Stimuli-Responsive Gels, PMMA-Based Composite Films, and UV-Shielding.

Lanthanide-based light-emitting coordination polymers (CPs) and CP gels (CPGs) have significance for applications in optical systems, image processing/multiplexing, and optical sensors. In this study, we report two new luminescent CPs (EuL-CP (1) and TbL-CP (2)) and CPGs (EuL-gel (5) and TbL-gel (6)) using lanthanide(III) ions (Ln(III) = Eu(III) and Tb(III)) and 4-(4-carboxyphenyl)-2,2:6,2-terpyridine ligand (L) capable of forming stable thermoreversible gels. Probable structures of EuL-CP (1) and TbL-CP (2) and the formations of EuL-gel (5) and TbL-gel (6) are proposed based on adequate computational studies. The CPGs are stimuli-responsive and could be utilized as invisible security inks for encryption. Further, poly(methyl methacrylate) (PMMA) polymer doped with respective CPs (0.75 wt %) is found to be suitable for forming composite films with UV-shielding properties.

Real-time plasma boundary shape reconstruction using visible camera on EAST Tokamak

Abstract Accurate plasma shape reconstruction is crucial for the stable operation of tokamak devices. In this study, a plasma optical boundary reconstruction system is constructed on the Experimental Advanced Superconducting Tokamak (EAST), and real-time shape reconstruction based on an optical method is realized for the first time on EAST.
First, a boundary extraction algorithm based on gray features is designed to extract the optical boundary from plasma optical images. Then, to reconstruct the optical boundary in the tokamak coordinate system, a camera calibration algorithm is developed based on feature point matching, and a coordinate mapping algorithm is designed based on plasma geometric features. Then, the system reconstructs the plasma boundary shape based on images acquired by cameras. Finally, the system is deployed in real-time on EAST, and its reconstruction rate meets the requirement of the EAST plasma shape control system. This study validates the feasibility of using an optical boundary shape reconstruction method on a tokamak device for real-time plasma shape reconstruction, providing a new shape reconstruction approach during steady-state discharge in future fusion devices.

Determining sources in the bioluminescence tomography problem

Abstract In this paper, we revisit the bioluminescence tomography\,(BLT) problem, where one seeks to reconstruct bioluminescence signals (an internal light source) from external measurements of the Cauchy data. As one kind of optical imaging, the BLT has many merits such as high signal-to-noise ratio, non-destructivity and cost-effectiveness etc., and has potential applications such as cancer diagnosis, drug discovery and development as well as gene therapies and so on. In the literature, BLT is extensively studied based on diffusion approximation (DA) equation, where the distribution of peak sources is to be reconstructed and no solution uniqueness is guaranteed without adequate a priori information. Motivated by the solution uniqueness issue, several theoretical results are explored. The major contributions in this work that are new to the literature are two-fold: first, we show the theoretical uniqueness of the BLT problem where the light sources are in the shape of $C^2$ domains or polyhedral- or corona-shaped; second, we support our results with plenty of problem-orientated numerical experiments.

Operando Optical Imaging of Cathode Swelling Process Inside Lithium Primary Batteries: Comparative Studies between Different Structured CFx.

As a crucial cathode material with ultrahigh theoretical capacity (865 mAh/g) and energy density (>2100 Wh/kg), fluorinated carbon (CFx) is promising for lithium primary batteries. However, the operating performance of CFx cathode is hindered by nonuniform volume expansion during discharging. To investigate this, we used operando confocal microscopy to visualize the thickness evolution of two different CFx cathodes and quantified their swelling ratios as a function of the discharge depth. Our findings show that CFx synthesized from hard carbon (FHC), featuring a disordered structure and abundant pores, exhibits a swelling ratio lower than that of conventional layered fluorinated graphite (FG). This is due to different electrochemical mechanisms: lithium enters FG interlayers nonuniformly through "edge propagation" pathways while lithiation occurs homogeneously in FHC, unraveled by single-particle Raman and photoluminescence measurement. This work enhances our understanding on CFx volume expansion, offering important opportunities to address the cathode swelling issue and optimize electrochemical performance in Li/CFx batteries.

Atomically Precise Fluorescent Gold Nanocluster as a Barrier-Permeable and Brain-Specific Imaging Probe.

Photonic nanomaterials play a crucial role in facilitating the necessary signal for optical brain imaging, presenting a promising avenue for early diagnosis of brain-related disorders. However, the blood-brain barrier (BBB) presents a significant challenge, blocking the entry of most molecules or materials from the bloodstream into the brain. To overcome this, photonic nanocrystals in the form of gold clusters (LAuC) with size less than 3 nm, have been developed, with Levodopa conjugated to LAuC (Dop@LAuC) for targeted brain imaging. Dop@LAuC crosses the BBB and emits in the near-infrared (NIR) wavelength, enabling real-time optical brain imaging. An in vitro BBB model using brain endothelial cells showed that 50 % of Dop@LAuC crossed the barrier within 3 hours, compared to only 10 % of LAuC, highlighting the enhanced ability of L-dopa-conjugated gold clusters to penetrate the BBB. In vivo optical imaging in healthy mice further confirmed the material's efficacy to cross BBB without compromising the barrier integrity.

Au-Doped Black Silicon Photodetector Fabricated by a Femtosecond Laser with Excellent Near-Infrared Response.

Silicon photonic devices are key components in optical imaging and sensing for communication, and the development of silicon-based photodetectors with ideal performance in the visible and infrared spectral ranges can promote the application of silicon photonics in various photoelectronic systems. Here, a Au-doped black silicon photodetector was prepared by a femtosecond laser direct writing technique. The conical micro-/nanostructures with different sizes were produced by different laser fluence irradiation. Ultrafast pump-probe technology revealed that the strong spallation process and phase explosion between Au and silicon facilitate the interfusion of Au atoms into the silicon lattice. EDS analyses, Raman spectra, and XPS spectra show the uniform distribution of Au elements, multiconfiguration amorphous phase transition, and stable chemical valence states of Au elements in Au-doped black silicon layers, respectively. The excellent geometric light trapping performance of the surface conic structure-assisted photodetector achieved a high absorptance of 95% in the 200-1100 nm band. Simultaneously, the introduction of the intermediate band by Au hyperdoping also leads to a strong absorptance of 75% in the 1100-2500 nm band. The photoelectrical response rate of the Au-doped black silicon photodetectors increased by 10 times in the infrared wavelength band by means of the introduced intermediate energy levels through Au element doping. The switching photocurrent ratio is also found to be boosted 10 times, which comes from the reduction of the photon injection barrier. The excellent photoelectronic properties lead to the increased potential of femtosecond laser processing for integration with photonics and electronics, which shows great possibilities in the further progress of energy devices, information technology, and artificial intelligence.

Optical imaging of the stochastic nucleation kinetics and intrinsic activation energy of single spin-crossover nanoparticles

Cooperative spin crossover (SCO) compounds are one of the most promising molecular bistable solids due to their intriguing thermal hysteresis phenomena around room temperature. It is well known that hysteresis is an essential kinetic effect, however, accurate assessment of the spin transition kinetics of SCO nanomaterials remains scarce. Herein, we developed a thermal-optical methodology to image the thermally induced spin transition kinetics of single SCO nanoparticles in a quantitative, repeatable, and high-throughput manner. Single-particle measurement revealed an intrinsic nucleation-dominated spin transition mechanism, where a highly stochastic nucleation process was clearly observed during the repeatable measurements. By quantifying the dependence of nucleation time on temperature, the activation energy barriers for nucleation were further extracted at a single particle level. Based on this foundation, the high throughput of the optical imaging not only contributed to uncovering the significant nanoparticle-to-nanoparticle heterogeneity, with implications for a negative correlation between apparent activation energy barriers for nucleation and size of the SCO nanoparticles, but also facilitated identifying a minority with high activation energy at least twice the average value. The extraordinary performance was then attributed to the fewer defects within their structures, as confirmed by further results from the in situ creation of defects by thermal ablation, thereby setting the lower limit for the intrinsic activation energy of ideal SCO crystals and promising their potential for future applications in high-performance molecular devices.

ANALYSIS OF OPTICAL COHERENCE TOMOGRAPHY DATA IN PATIENTS WITH VARIOUS VARIANTS OF THE GLAUCOMA PROCESS

Today, about 537 million people in the world aged 20 to 79 suffer from diabetes mellitus, in 3% of cases neovascular glaucoma is diagnosed, threatening vision loss. Neovascular glaucoma is one of the most aggressive forms of secondary glaucomas and is often refractory to standard treatment methods. In domestic and foreign literature, there is no single standard for choosing the tactics of surgical treatment of patients with neovascular glaucoma against the background of diabetic retinopathy. In this regard, studies aimed at studying the morphofunctional parameters of eyes with neovascular glaucoma against the background of diabetic retinopathy acquire not only theoretical but also obvious practical interest. In the course of further development of methods for complex effects on eye structures to reduce intraocular pressure and progression of the glaucoma process. An analysis of optical coherence tomography images of 51 patients (51 eyes) was conducted, and the main aspects were identified for further use in choosing the tactics of surgical intervention.

Fabrication, characterization, and 3D printing of high-internal phase Pickering emulsion stabilized by heat-treated copra protein and calcium composite.

HCP-Ca nanoparticles were prepared by incorporating varying concentrations of CaCl2 into heated copra protein (HCP). The results showed a positive correlation between Ca2+ concentration and turbidity, indicating greater HCP aggregation with increasing Ca2+ levels. Microscopy analysis revealed that HCP-Ca nanoparticles had a rough surface morphology. Intermolecular forces such as disulfide bonds, hydrophobic interactions, and hydrogen bonds were key in the conformation of HCP aggregates, with calcium ions enhancing stability by forming salt bridges. HCP-Ca nanoparticle-based high internal phase Pickering emulsions (HIPPEs) were also fabricated using homogenization-centrifugation treatment. The nanoparticles showed contact angles of 87.8° to 98.3°, particle sizes between 80.42 and 80.95 nm, and the HIPPEs had zeta potentials ranging from -23 to -39 mV. The addition of Ca2+ enhanced stability by forming salt bridges, reducing particle size, and altering size distributions. Rheological and texture analysis showed that Ca2+ addition significantly improved the viscoelasticity of HCP-Ca nanoparticle-based HIPPEs, as well as increasing hardness and adhesiveness. Optical microscopy and magnetic imaging techniques revealed details about emulsion formation and oil-water distribution in HCP-Ca nanoparticle-based HIPPEs. The excellent printing stability and structural versatility of HCP-Ca nanoparticle-based HIPPEs allowed the formation of complex 3D structures, offering a valuable approach for fabricating processable and editable HIPPEs from waste materials. This paper aims to develop a food-grade copra protein-based Pickering HIPPE and explore differences in fabrication methods, providing new insights into the design of innovative Pickering stabilizers.

Trop2-Targeted Molecular Imaging in Solid Tumors: Current Advances and Future Outlook.

Trophoblast cell surface antigen 2 (Trop2), a transmembrane glycoprotein, plays a dual role in physiological and pathological processes. In healthy tissues, Trop2 facilitates development and orchestrates intracellular calcium signaling. However, its overexpression in numerous solid tumors shifts its function toward driving cell proliferation and metastasis, thus leading to a poor prognosis. The clinical relevance of Trop2 is underscored by its utility as both a biomarker for diagnostic imaging and a target for therapy. Notably, the U.S. Food and Drug Administration (FDA) has approved sacituzumab govitecan (SG), a novel Trop2-targeted agent, for treating triple-negative breast cancer (TNBC) and refractory urothelial cancer, highlighting the significance of Trop2 in clinical oncology. Molecular imaging, a powerful tool for visualizing and quantifying biological phenomena at the molecular and cellular levels, has emerged as a critical technique for studying Trop2. This approach encompasses various modalities, including optical imaging, positron emission tomography (PET), single photon emission computed tomography (SPECT), and targeted antibodies labeled with radioactive isotopes. Incorporating Trop2-targeted molecular imaging into clinical practice is vital for the early detection, prognostic assessment, and treatment planning of a broad spectrum of solid tumors. Our review captures the latest progress in Trop2-targeted molecular imaging, focusing on both diagnostic and therapeutic applications across diverse tumor types, including lung, breast, gastric, pancreatic, prostate, and cervical cancers, as well as salivary gland carcinomas. We critically evaluate the current state by examining the relevant applications, diagnostic accuracy, therapeutic efficacy, and inherent limitations. Finally, we analyze the challenges impeding widespread clinical application and offer insights into strategies for advancing the field, thereby guiding future research endeavors.

Machine learning enabled fast optical identification and characterization of 2D materials.

Two-dimensional materials are a class of atomically thin materials with assorted electronic and quantum properties. Accurate identification of layer thickness, especially for a single monolayer, is crucial for their characterization. This characterization process, however, is often time-consuming, requiring highly skilled researchers and expensive equipment like atomic force microscopy. This project aims to streamline the identification process by using machine learning to analyze optical images and quickly determine layer thickness. In this paper, we evaluate the performance of three machine learning models - SegNet, 1D U-Net, and 2D U-Net- in accurately identifying monolayers in microscopic images. Additionally, we explore labeling and image processing techniques to determine the most effective and accessible method for identifying layer thickness in this class of materials.

Foundation models for fast, label-free detection of glioma infiltration.

A critical challenge in glioma treatment is detecting tumour infiltration during surgery to achieve safe maximal resection1-3. Unfortunately, safely resectable residual tumour is found in the majority of patients with glioma after surgery, causing early recurrence and decreased survival4-6. Here we present FastGlioma, a visual foundation model for fast (<10 s) and accurate detection of glioma infiltration in fresh, unprocessed surgical tissue. FastGlioma was pretrained using large-scale self-supervision (around 4 million images) on rapid, label-free optical microscopy, and fine-tuned to output a normalized score that indicates the degree of tumour infiltration within whole-slide optical images. In a prospective, multicentre, international testing cohort of patients with diffuse glioma (n = 220), FastGlioma was able to detect and quantify the degree of tumour infiltration with an average area under the receiver operating characteristic curve of 92.1 ± 0.9%. FastGlioma outperformed image-guided and fluorescence-guided adjuncts for detecting tumour infiltration during surgery by a wide margin in a head-to-head, prospective study (n = 129). The performance of FastGlioma remained high across diverse patient demographics, medical centres and diffuse glioma molecular subtypes as defined by the World Health Organization. FastGlioma shows zero-shot generalization to other adult and paediatric brain tumour diagnoses, demonstrating the potential for our foundation model to be used as a general-purpose adjunct for guiding brain tumour surgeries. These findings represent the transformative potential of medical foundation models to unlock the role of artificial intelligence in the care of patients with cancer.

Retraction Note: Intravascular optical imaging for early detection of coronary artery disease in asymptomatic patients

Retraction Note: Intravascular optical imaging for early detection of coronary artery disease in asymptomatic patients