Light Imaging Research Articles

The Role of Indocyanine Green With Near-Infrared Imaging for the Intraoperative Detection and Enhancement of Endometriosis Lesions: A Narrative Review.

Background: There is a clinical need for improved intraoperative detection of endometriosis, and the use of Indocyanine Green with Near-Infrared Imaging (NIR-ICG) is a novel technique for this purpose. The aim of this review is to determine whether NIR-ICG is an effective tool for endometriosis detection and establish an evidence-based methodology for its use.Methods: This review searches Ovid MEDLINE and Embase through July 2023 and considers primary literature published in English describing the use of NIR-ICG to detect endometriosis intraoperatively. Case studies, video demonstrations and articles describing NIR-ICG used for other surgical roles were not considered. Identified studies were screened independently by two authors, and data was extracted by a single author.Results: NIR-ICG was found to enhance the detection of endometriosis in six out of the nine included studies with additional lesion identification, and to have an unchanged or reduced efficacy compared to current standards in the remaining three. Across all studies there were lesions missed by NIR-ICG which were detected by conventional imaging. A greater duration of time between dye administration and visualisation of lesions was found to be more effective for detection. The ideal ICG protocol proposed from this review is a fixed amount of dye proportional to patient weight prior to surgery (0.25-0.3 mg/kg) followed by a longer waiting time before imaging (10-30 min).Conclusion: NIR-ICG has a possible role to enhance the identification of endometriosis intraoperatively as an adjunct to conventional white light imaging, particularly deeper infiltrating disease. However, substantial further research is required in this field.

A Dataset of Visible Light and Thermal Infrared Images for Health Monitoring of Caged Laying Hens in Large-Scale Farming.

Considering animal welfare, the free-range laying hen farming model is increasingly gaining attention. However, in some countries, large-scale farming still relies on the cage-rearing model, making the focus on the welfare of caged laying hens equally important. To evaluate the health status of caged laying hens, a dataset comprising visible light and thermal infrared images was established for analyses, including morphological, thermographic, comb, and behavioral assessments, enabling a comprehensive evaluation of the hens' health, behavior, and population counts. To address the issue of insufficient data samples in the health detection process for individual and group hens, a dataset named BClayinghens was constructed containing 61,133 images of visible light and thermal infrared images. The BClayinghens dataset was completed using three types of devices: smartphones, visible light cameras, and infrared thermal cameras. All thermal infrared images correspond to visible light images and have achieved positional alignment through coordinate correction. Additionally, the visible light images were annotated with chicken head labels, obtaining 63,693 chicken head labels, which can be directly used for training deep learning models for chicken head object detection and combined with corresponding thermal infrared data to analyze the temperature of the chicken heads. To enable the constructed deep-learning object detection and recognition models to adapt to different breeding environments, various data enhancement methods such as rotation, shearing, color enhancement, and noise addition were used for image processing. The BClayinghens dataset is important for applying visible light images and corresponding thermal infrared images in the health detection, behavioral analysis, and counting of caged laying hens under large-scale farming.

Noise sensitivity analysis of focal scanning light field imaging

Light field imaging can simultaneously record spatial and angular information of light signals to provide various computational imaging functions. However, traditional microlens array-based light field cameras usually suffer from a trade-off between spatial and angular resolutions. In contrast, focal scanning light field imaging (FSLFI) can digitally modulate an incident light field through an image stack captured at different focal planes and then utilize the transport-of-intensity property to computationally recover the full-resolution light field. This paper presents a unified light field reconstruction algorithm framework, which involves different types of algorithms, such as back-projection reconstruction and additive/multiplicative iterative reconstruction, for FSLFI. Based on the unified algorithm framework, we systematically analyze and investigate the FSLFI performance on noise sensitivity. Light fields are reconstructed at different noise levels to quantitatively analyze the FSLFI performances with different types of algorithms. Both simulation and actual experimental results demonstrate that the noise sensitivity and reconstruction accuracy are constrained by each other for FSLFI. Back-projection reconstruction is appropriate in high-efficiency light field reconstruction, while additive/multiplicative iterative reconstruction is suitable for high-accuracy light field imaging at high/low noise levels. These conclusions can apply to any FSLFI method covered by the unified algorithm framework, in which appropriate algorithms can be selected for high-quality light field imaging and measurement according to specific application scenarios.

Dataset of human skin and fingernails images for non-invasive haemoglobin level assessment

Anaemia, a decrease in total concentration of haemoglobin (Hb) in blood, affects substantial percentage of the population worldwide. Currently, the gold standard for determining the Hb level is the invasive analysis of venous blood. Yet, more and more research groups demonstrate the possibility of non-invasive Hb assessment using white light imaging of tissue sites where Hb is the main chromophore, in particular, fingernails. Despite the promising declarations, non-invasive Hb assessment via RGB-imaging is still poorly used in practice. The main reason is the difficulty in establishing the true accuracy of the methods presented in different works since they are tested on private datasets collected under different experimental conditions. Here we present an open dataset containing RGB images of skin and fingernails for patients with a known level of Hb, thus providing a single benchmark for researchers and engineers in the field, aimed at fostering translation of non-invasive imaging methods to the bedside.

Multicentre study to assess the performance of an artificial intelligence instrument to support qualitative diagnosis of colorectal polyps

ObjectiveComputer-aided diagnosis (CAD) using artificial intelligence (AI) is expected to support the characterisation of colorectal lesions, which is clinically relevant for efficient colorectal cancer prevention. We conducted this study to...

Optical signal characteristics analysis of atmospheric disturbance density fields generated by high-speed aircraft

Aircraft disturbs the adjacent atmospheric environment in flight, forming spatial distribution features of atmospheric density that differ from the natural background, which may potentially be utilized as tracer characteristics to introduce new technologies for indirectly sensing the presence of aircraft. In this paper, the concept of a long-range aircraft detection based on the atmospheric disturbance density field is proposed, and the detection mode of tomographic imaging of the scattering light of an atmospheric disturbance flow field is designed. By modeling the spatial distribution of the disturbance density field, the scattered echo signal images of active light towards the disturbance field at long distance are simulated. On this basis, the characteristics of the disturbance optical signal at the optimal detection resolution are analyzed. The results show that the atmospheric disturbance flow field of the supersonic aircraft presents circular in the light-scattering echo images. The disturbance signal can be further highlighted by differential processing of the adjacent scattering images. As the distance behind the aircraft increases, the diffusion range of the disturbance signal increases, and the signal intensity and contrast with the background decrease. Under the ground-based observation conditions of the aircraft at a height of 10000 m, a Mach number of 1.6, and a detection distance of 100 km, the contrast between the disturbance signal and the background was 30 dB at a distance of one time from the rear of the fuselage, and the diffusion diameter of the disturbance signal was 50 m. At a distance eight times the length of the aircraft, the contrast decreased to 10 dB, and the diameter increased to 290 m. The contrast was reduced to 3 dB at a distance nine times the length of the aircraft, and the diameter was diffused to 310 m. These results indicate the possibility of long-range aircraft detection based on the characteristics of the atmospheric density field.

Experimental three-dimensional location and size distribution of rising bubbles in a cylindrical column through light field imaging

Experimental three-dimensional location and size distribution of rising bubbles in a cylindrical column through light field imaging

Oogenesis and Spermatogenesis of the Triploid Black Tiger Shrimp, Penaeus monodon

Triploidy (3n) induction of Penaeus monodon was performed separately by Australian and Thai groups of researchers 14 years ago, incidentally at the same period. The Australian group employed the chemical induction method, while the Thai group the cold shock one, and both groups obtained 3n P. monodon in their attempts. The success has led to several studies on the physiology of the 3n P. monodon, including growth, survival and reproductive functions. Both groups reported sterility of the 3n shrimp. The Australian group reported defected oogenesis and spermatogenesis of the 3n shrimp examined at subadult stage. Since the evaluation of the reproductive functions should be performed at the adult stage of the animals, we, therefore, performed in-depth studies on oogenesis and spermatogenesis of adult 3n P. monodon induced by cold shock. The studies include gross observation of the ovary, light (LM) and transmission electron (TEM) microscopy and image analysis of sex cells. The ovary of the 3n P. monodon females could not develop to full-maturation and their gonadosomatic index (GSI) was significantly lower than that of the 2n shrimp. Oogenesis of the 3n females proceeded from oogonia to cortical rod oocytes, but with significantly lower percentage than that of the 2n shrimp. The GSI of the 3n males was significantly lower than that of the 2n shrimp. Their spermatogenesis, however, proceeded normally from spermatogonia to spermatozoa, but with low density of spermatozoa in the seminiferous tubule and vas deferens, and none in the terminal ampoule. The average nuclear area of the 3n spermatozoa was significantly lower than that of the 2n shrimp as well. Altogether, these results suggest that 3n P. monodon induced by cold shock had defect in both oogenesis and spermatogenesis, probably more in quantity than in quality. HIGHLIGHTS Oogenesis and spermatogenesis of the triploid black tiger shrimp, monodon, induced by cold shock were studied. The study found abnormalities in the spermatogenesis, but not oogenesis, of the triploid P. monodon induced by cold shock. It may be concluded that triploidy condition of P. monodon induced by cold shock affects meiotic, but not mitotic activity of the sex cells. GRAPHICAL ABSTRACT

FusionOC: Research on optimal control method for infrared and visible light image fusion

Infrared and visible light image fusion can solve the limitations of single-type visual sensors and can boost the target detection performance. However, since the traditional fusion strategy lacks the controllability and feedback mechanism, the fusion model cannot precisely perceive the relationship between the requirements of the fusion task, the fused image quality, and the source image features. To this end, this paper establishes a fusion model based on the optimal controlled object and control mode called FusionOC. This method establishes two types of mathematical models of the controlled objects by verifying the factors and conflicts affecting the quality of the fused image. It combines the image fusion model with the quality evaluation function to determine the two control factors separately. At the same time, two proportional-integral-derivative (PID) control and regulation modes based on the backpropagation (BP) neural network are designed according to the control factor characteristics. The fusion system can adaptively select the regulation mode to regulate the control factor according to the user requirements or the task to make the fusion system perceive the connection between the fusion task and the result. Besides, the fusion model employs the feedback mechanism of the control system to perceive the feature difference between the fusion result and the source image, realize the guidance of the source image feature to the entire fusion process, and improve the fusion algorithm's generalization ability and intelligence level when handling different fusion tasks. Experimental results on multiple public datasets demonstrate the advantages of FusionOC over advanced methods. Meanwhile, the benefits of our fusion results in object detection tasks have been demonstrated.

S915 Comparison of Red Dichromatic Imaging With Standard White Light Imaging in Hemostatic Treatment During Endoscopic Interventions: A Systematic Review and Meta-Analysis

S915 Comparison of Red Dichromatic Imaging With Standard White Light Imaging in Hemostatic Treatment During Endoscopic Interventions: A Systematic Review and Meta-Analysis

Eagle syndrome: tissue characteristics and structure of the styloid process.

Eagle syndrome is a bone disease where elongation of the styloid process leads to throat and neck pain, and in severe cases neurovascular symptoms such as syncope and neuralgia. The pathophysiology of Eagle syndrome is poorly understood with various theories having been proposed how this elongation is caused. To better understand the pathophysiology, we performed a work-up in 6 patients presenting with Eagle syndrome. Patients mainly presented with pain on turning the neck (100%), foreign body sensation (67%), tension in the neck (67%), and dysphagia (50%). The typical length of the styloid process ranges from 25 to 30 mm; however, [18F]NaF (sodium fluoride) PET/CT showed elongated styloid processes with an average length of 52.1 ± 15.6mm (mean ± SD) with increased turnover at the base of one of the styloid processes. The removed styloid processes were further examined by histology, micro-CT, quantitative backscatter electron imaging (qBEI), Fourier transform infrared spectroscopy (FTIR), and circularly polarized light imaging. Histology revealed one case of a fractured styloid process healing through callus formation and one case of pseudarthrosis. Bone mineral density and mineralization was similar in the styloid processes when compared to cortical bone samples derived from the mandibular bone of different patients. Circular polarized light microscopy showed a collagen orientation in the styloid process comparable to the cortical bone samples with a distinct separation of collagen structure between the mineralized structure and the surrounding soft tissue with FTIR analysis demonstrating a typical composition of bone. This altogether suggests that the elongated styloid processes in Eagle syndrome are mature bone, capable of endochondral repair, possibly growing from the base of the process through endochondral ossification, rather than being a form of secondary calcification of the stylohyoid ligament as previously postulated.

Multi-diagnostic of dust growth in a capacitive Ar/C2H2 plasma

Abstract The interest in the production of nanoparticles (NPs) within Ar/C2H2 reactive plasmas is increasing, driven by their potential applications in functional materials or for their analogy to cosmic dust. The growth process of NPs has been thoroughly examined using a broad array of diagnostic tools. Significant among these tools are those that determine two-dimensional distributions of NP sizes and densities. The inherent complexity of these techniques has resulted in a limited number of works that integrate these measurements with a multitude of other diagnostic tools. Here, we show a multi-diagnostic exploration of the growing process of NPs in Ar/C2H2 plasmas. The combination of in-situ techniques, such as scattered light images, optical emission spectroscopy, light extinction, quadrupole mass signals, or self-bias voltage, with ex-situ scanning electron microscopy images and FTIR spectra of the deposited dust, provides a detailed picture of the growth process. The temporal evolution of plasma parameters, coupled with chemical composition measurements, provides a comprehensive description of the dust growth phases, and the FTIR measurements reveal an appreciable difference in chemical composition between the core and shell of the NPs. Furthermore, employing a method based on the terminal falling velocity of NPs in the afterglow, the intrinsic mass density of NPs is estimated. The asymmetries observed in the spatial distributions of NP size and density are qualitatively discussed in terms of neutral drag, ion drag, and electrostatic forces.

3D Radiation-hydrodynamical Simulations of Shadows on Transition Disks

Shadows are often observed in transition disks, which can result from obscuring by materials closer to the star, such as a misaligned inner disk. While shadows leave apparent darkened emission as observational signatures, they have significant dynamical impact on the disk. We carry out 3D radiation-hydrodynamical simulations to study shadows in transition disks and find that the temperature drop due to the shadow acts as an asymmetric driving force, leading to spirals in the cavity. These spirals have zero pattern speed following the fixed shadow. The pitch angle is given by tan−1(c s /v ϕ ) (6° if h/r = 0.1). These spirals transport mass through the cavity efficiently, with α ∼ 10−2 in our simulation. Besides spirals, the cavity edge can also form vortices and flocculent streamers. When present, these features could disturb the shadow-induced spirals. By carrying out Monte Carlo radiative transfer simulations, we show that these features resemble those observed in near-infrared scattered light images. In the vertical direction, the vertical gravity is no longer balanced by the pressure gradient alone. Instead, an azimuthal convective acceleration term balances the gravity–pressure difference, leading to azimuthally periodic upward and downward gas motion reaching 10% of the sound speed, which can be probed by Atacama Large Millimeter/submillimeter Array line observations.

Low‐light image enhancement via lightweight custom non‐linear transform network

AbstractConvolutional neural network (CNN)‐based models have shown significant progress in low light image enhancement. However, many existing models possess a large number of parameters, making them unsuitable for deployment on terminal devices. Moreover, adjustments to brightness, contrast, and colour in images are often non‐linear, and convolution is not the best at capturing complex non‐linear relationships in image data. To address these issues, a model based on an end‐to‐end custom non‐linear transform network (CNTNet) is proposed. CNTNet combines a custom non‐linear transform layer with CNN layers to achieve image contrast and detail enhancement. The CNT layer in this model introduces transformation parameters at multiple scales to manipulate input images within various ranges. CNTNet progressively processes images by stacking multiple non‐linear transform layers and convolutional layers while integrating residual connections to capture and leverage subtle image features. The final output is generated through convolutional layers to obtain enhanced images. Experimental results of CNTNet demonstrate that, while maintaining a comparable level of image quality evaluation metrics to mainstream models, it significantly reduces the parameter count to only 2K.

Modelling non-radially propagating coronal mass ejections and forecasting the time of their arrival at Earth

We present the study of two solar eruptive events observed on December 7 2020 and October 28 2021. Both events were associated with full halo coronal mass ejections (CMEs) and flares. These events were chosen because they show a strong non-radial direction of propagation in the low corona and their main propagation direction observed in the inner heliosphere is not fully aligned with the Sun-Earth line. This characteristic makes them suitable for our study, which aims to inspect how the non-radial direction of propagation in the low corona affects the time of CMEs’ arrival at Earth. We reconstructed the CMEs using SOHO/LASCO and STEREO/COR observations and modelled them with the 3D MHD model EUHFORIA and the cone model for CMEs. In order to compare the accuracy of forecasting the CME and the CME-driven shock arrival time at Earth obtained from different methods, we also used so-called type II bursts, radio signatures of associated shocks, to find the velocities of the CME-driven shocks and forecast the time of their arrival at Earth. Additionally, we estimated the CME arrival time using the 2D CME velocity obtained from the white light images. Our results show that the lowest accuracy of estimated CME Earth arrival times is found when the 2D CME velocity is used (time difference between observed and modelled arrival time, Δt ≈ −29 h and −39 h, for the two studied events, respectively). The velocity of the type II radio bursts provides somewhat better – but still not very accurate – results (Δt ≈ +21 h and −29 h, for the two studied events, respectively). Employing, as an input to EUHFORIA, the CME parameters obtained from the graduated cylindrical shell (GCS) fittings at consequently increasing heights, results in a strongly improved accuracy of the modelled CME and shock arrival time; Δt changes from 20 h to 10 min in the case of the first event, and from 12 h to 30 min in the case of the second one. This improvement shows that when we increased the heights of the GCS reconstruction we accounted for the change in the propagation direction of the studied CMEs, which allowed us to accurately model the CME flank encounter at Earth. Our results show the great importance of the change in the direction of propagation of the CME in the low corona when modelling CMEs and estimating the time of their arrival at Earth.

Overexpression of SEZ6L2 and Immune Infiltration in Cancer Based on Gene Image Diagnosis.

With the rapid advancement of optical image diagnostic technology, researchers are delving into the potential applications in the field of cancer diagnosis and treatment. The exact link between the SEZ6L2 gene and cancer immune infiltration remains elusive. This study aims to investigate the relationship between SEZ6L2 gene overexpression and cancer immune infiltration using optical image diagnostic technology, thereby presenting novel insights for enhancing cancer diagnosis and treatment strategies. Tissue samples obtained from cancer patients were meticulously analyzed to quantitatively assess the expression of the SEZ6L2 gene through light image diagnostic technology. Additionally, immunohistochemical techniques were employed to assess the nature and quantity of immune infiltrating cells within the cancerous tissues. The enrichment pathways were found to include complement activation, circulating immunoglobulin mediated humoral immune response, protein activation cascade, immunoglobulin complex, and immunoglobulin. In addition, the expression of SEZ6L2 is closely related to the infiltration level of tumor infiltrating immune cells (TIICs), and there is a potential relationship between the expression of SEZ6L2 and different marker genes of TIIC. Increased SEZ6L2 mRNA expression in breast invasive carcinoma was significantly associated with negative prognosis and immune invasion. SEZ6L2 may be a novel prognostic biomarker and a potential immunotherapeutic target in BRCA.

Texture Analysis and Classification using Local Binary Patterns and Statistical Features

Texture analysis and classification are crucial in many applications such as medical applications, satellite imagery analysis, and so on. This paper presents a new technique that incorporates the LBP with the HOG to improve the texture analysis and classification. LBP is famous for finding out the local texture descriptors by comparing the pixel intensities it deals with and can challenge light variations and image transformations. On the other hand, there is HOG which emphasizes edge and gradient information to detect the orientation and shape of a texture in a given image. While LBP describes the local micro-patterns HOG gives the perspective of the global gradient orientation. The combined use of local and global texture information is helpful in the presented problem when prioritizing the recognition of complex texture patterns that cannot be deciphered by a single algorithm. To demonstrate the efficiency of the proposed hybrid method, several experiments are performed on several texture databases. According to the findings, the proposed LBP-HOG strategy proves more beneficial than basic LBP and HOG techniques concerning the classification rate and computing time. The combination method shows improved performance in terms of agreement with the reference of fine and coarse level of texture descriptions along with providing large-scale description of the texture which results in the improved discriminatory power of the texture classes.

Studies on type material from Kützing’s diatom collection VIII. Species assigned to the genera Epithemia Brébisson ex Kützing and Rhopalodia O. Müller

We detail the diatom taxa described by F.T. Kützing across three of his publications that have been referred to the diatom genera Epithemia and Rhopalodia. Taxa considered include Frustulia adnata, F. picta, E. alpestris, E. musculus, E. porcellus, E. proboscidea, E. sorex, E. ventricosa, E. vertagus, E. ventricosa β. gregaria and E. reticulata. For these 12 taxa, this represents the first time Kützing’s specimens have been illustrated with light microscopy. Most of the material consulted here is from the Natural History Museum, London, though we also reviewed material from the Academy of Natural Sciences for E. adnata. We present light microscope images of the Kützing taxa and complement these observations with images of the type slides, material packets and both herbarium (unpublished) and published drawings. In some cases, modern concepts of Kützing species are supported, but in others it is likely that species concepts will be changed by the specimens in the type material. Lectotypes are designated for Epithemia adnata and Epithemia reticulata.

Spectrum aided vision enhancer enhances mucosal visualization by hyperspectral imaging in capsule endoscopy.

Narrow-band imaging (NBI) is more efficient in detecting early gastrointestinal cancer than white light imaging (WLI). NBI technology is available only in conventional endoscopy, but unavailable in magnetic-assisted capsule endoscopy (MACE) systems due to MACE's small size and obstacles in image processing issues. MACE is an easy, safe, and convenient tool for both patients and physicians to avoid the disadvantages of conventional endoscopy. Enabling NBI technology in MACE is mandatory. We developed a novel method to improve mucosal visualization using hyperspectral imaging (HSI) known as Spectrum Aided Visual Enhancer (SAVE, Transfer N,Hitspectra Intelligent Technology Co., Kaohsiung, Taiwan). The technique was developed by converting the WLI image captured by MACE to enhance SAVE images. The structural similarity index metric (SSIM) between the WLI MACE images and the enhanced SAVE images was 91%, while the entropy difference between the WLI MACE images and the enhanced SAVE images was only 0.47%. SAVE algorithm can identify the mucosal break on the esophagogastric junction in patients with gastroesophageal reflux disorder. We successfully developed a novel image-enhancing technique, SAVE, in the MACE system, showing close similarity to the NBI from the conventional endoscopy system. The future application of this novel technology in the MACE system can be promising.

Model based optimization for refractive index mismatched light sheet imaging

Selective plane illumination microscopy (SPIM) is an optical sectioning imaging approach based on orthogonal light pathways for excitation and detection. The excitation pathway has an inverse relation between the optical sectioning strength and the effective field of view (FOV). Multiple approaches exist to extend the effective FOV, and here we focus on remote focusing to axially scan the light sheet, synchronized with a CMOS camera’s rolling shutter. A typical axially scanned SPIM configuration for imaging large samples utilizes a tunable optic for remote focusing, paired with air objectives focused into higher refractive index media. To quantitatively explore the effect of remote focus choices and sample space refractive index mismatch on light sheet intensity distributions, we developed an open-source computational approach for integrating ray tracing and field propagation. We validate our model’s performance against experimental light sheet profiles for various SPIM configurations. Our findings indicate that optimizing the position of the sample chamber relative to the excitation optics can enhance image quality by balancing aberrations induced by refractive index mismatch. We validate this prediction using a home-built, large sample axially scanned SPIM configuration and calibration samples. Our open-source, extensible modeling software can easily extend to explore optimal imaging configurations in diverse light sheet imaging settings.