Search Results (459)

Dry eye disease (DED) is a common condition that can be associated with cataract surgery, requiring pre- and postoperative considerations. Pre-existent DED and disruption of the tear film homeostasis due to incisional corneal nerve damage, intra-operative ocular surface drying, microscope phototoxicity, or the toxic effects of preservatives and active ingredients of postoperative drops or a combination thereof, represents a potential mechanism for worsening or developing DED after cataract surgery. Recent diagnostic advancements have enabled us better to understand the pathophysiology of DED after cataract surgery. For patients with pre-existing DED before cataract surgery, early intervention can improve surgical outcomes. In contrast, failure to recognize DED risk factors or subtle signs can result in inaccurate refractive measurements, poor surgical outcomes, including serious complications, worsening of dry eye symptoms, patient dissatisfaction, and decreased quality of life. This review presents an overview of the perioperative management of DED in patients undergoing cataract surgery with an emphasis on pre-operative diagnosis and treatment, and its impact on improving surgical refractive outcomes and decreasing complications. Full article

Image-Based Overlay (IBO) equipment leverages optical reflection imaging principles, combined with focusing and alignment strategies to measure overlay marks. Among all measurement steps, the focal plane measurement of marks exerts the most critical impact on overlay accuracy, while the time consumed by focal plane detection directly determines the overall measurement throughput. To address the trade-off between accuracy and efficiency in advanced process nodes, this paper proposes an integrated optimization strategy encompassing optical hardware design and software algorithms. The hardware solution adopts a dual-wavelength, dual-detector architecture: optimal imaging wavelengths are selected independently for the previous-layer and current-layer marks, ensuring each layer achieves ideal imaging conditions without mutual interference. The software strategy employs a deep learning framework to simultaneously predict and adjust the horizontal position (alignment) and vertical defocus number of measured marks in real time with high precision, thereby securing the optimal imaging posture. By synergizing hardware-based optimal imaging conditions and software-based posture adjustment, this method effectively mitigates the impact of background noise and system aberrations, ultimately improving both the accuracy and efficiency of overlay measurement. Full article

Adaptive optics (AO) aims to counteract wavefront distortions caused by atmospheric turbulence and inherent system errors. Aberration recovery accuracy and computational speed play crucial roles in its correction capability. To address the issues of slow wavefront aberration detection speed and low measurement accuracy in current wavefront sensorless adaptive optics, this paper proposes a wavefront correction method based on the EfficientNetV2-S model. The method utilizes paired focal plane and defocused plane intensity images to directly extract intensity features and reconstruct phase information in a non-iterative manner. This approach enables the direct prediction of wavefront Zernike coefficients from the measured intensity images, specifically for orders 3 to 35, significantly enhancing the real-time correction capability of the AO system. Simulation results show that the root mean square error (RMSE) of the predicted Zernike coefficients for D/r₀ values of 5, 10, and 15 are 0.038λ, 0.071λ, and 0.111λ, respectively, outperforming conventional convolutional neural network (CNN), ResNet50/101 and ConvNeXt-T models. The experimental results demonstrate that the EfficientNetV2-S model maintains good wavefront reconstruction and prediction capabilities at D/r₀ = 5 and 10, highlighting its high precision and robust wavefront prediction ability. Compared to traditional iterative algorithms, the proposed method offers advantages such as high precision, fast computation, no need for iteration, and avoidance of local minima in processing wavefront aberrations. Full article

Diffractive deep neural networks (D²NNs) have garnered significant attention for their ultra-low energy consumption and parallel optical computing capabilities. However, their practical deployment is hindered by the “model–reality” gap caused by fabrication inaccuracy, device fluctuation, assembly misalignment, environmental perturbation, etc. Here, we propose a combined framework that integrates sharpness-aware minimization (SAM) and aberration-immune learning (AIL), enabling joint immunity against both stochastic noise and systematic deviations from theoretical model training. Specifically, we show that under multiple perturbations such as salt-and-pepper noise, Gaussian noise, and wavefront aberration, the SAM–AIL framework achieves significant classification accuracy improvements on MNIST and Fashion-MNIST compared to conventional offline training approaches. D²NN trained with the SAM–AIL scheme exhibited significant accuracy enhancement under moderate salt-and-pepper noise, Gaussian noise, X-axis, and Y-axis tilting perturbations, respectively. Our work provides an efficient solution for offline training and deploying high-robustness D²NNs on realistic physical systems that are resilient to a variety of imperfections, significantly enhancing model transferability and reliability for optical computing tasks. Full article

In high-precision optical systems such as laser optics, astronomical observation, and semiconductor lithography, anti-reflection coatings are crucial for light transmittance, imaging quality, and stability, but traditional designs face modeling challenges in balancing ultralow reflectivity, high wavefront quality, and manufacturability amid multi-dimensional parameter coupling and multi-objective constraints. This study addresses these by proposing a unified mathematical modeling framework integrating a Symmetric five-layer high-low refractive index alternating structure (V-H-V-H-V) with dual-scale nanostructures, employing a constrained quasi-Newton optimization algorithm (L-BFGS-B) to minimize reflectivity, wavefront root-mean-square (RMS) error, and surface roughness root-mean-square (RMS) in a six-dimensional parameter space. The Sellmeier equation is adopted to calculate wavelength-dependent material refractive indices, the model uses the transfer matrix method for the Symmetric five-layer high-low refractive index alternating structure’s reflectivity, incorporates nano-surface height function gradient correction, sub-wavelength modulation, and radial optimization, applies Zernike polynomials for low-order aberration correction, quantifies surface roughness via curvature proxies, and optimizes via a weighted objective function prioritizing low reflectivity. Numerical results show the spatial average reflectivity at 632.8 nm reduced to 0.13%, the weighted average reflectivity across five representative wavelengths in the 550–720 nm range to 0.037%, the reflectivity uniformity to 10.7%, the post-correction wavefront RMS to 11.6 milliwavelengths, and the surface height standard deviation to 7.7 nm. This framework enhances design accuracy and efficiency, suits UV nanoimprinting and electron beam evaporation, and offers significant value for high-power lasers, lithography, and space-borne radars. Full article

Background/Objectives: Premium intraocular lenses (IOLs) are increasingly being selected for cataract and refractive lens surgery, but their functional performance depends critically on pupil size and corneal spherical aberration (SA). This study evaluates how these factors modulate the optical behavior of the RayOne EMV and Tecnis Synergy using a profilometry-based Through Object modulation transfer function (TO MTF) analysis. Methods: The surface profiles of the RayOne EMV and Tecnis Synergy were measured with a confocal optical profilometer and implemented in pseudophakic eye models via ray tracing. TO MTF at 50 cycles/mm was computed for object vergences from −4.0 D to +2.0 D over entrance pupil diameters from 2.0 to 5.5 mm in three corneal configurations derived from the Liou–Brennan model and ISO recommendations: mean population SA, aberration-free, and a myopic LASIK-like oblate cornea. Simulated optotype images were generated to relate TO MTF values to the expected distant, intermediate, and near visual performances. Results: RayOne EMV delivered high-quality distant image performance in all models. Its depth of focus increased only modestly and showed a strong dependence on pupil size. Intermediate and near vision rarely reached clinically acceptable levels. The Tecnis Synergy produced a broad depth-of-field plateau in distant to near visual performance for mean population spherical aberration at a 3.5 mm pupil. However, image quality at 90 cm remained limited. Optical performance worsened with increasing pupil size and positive spherical aberration, particularly under post-myopic LASIK conditions. Conclusions: The RayOne EMV behaves predominantly as a distance-oriented design with minimal true presbyopic benefit; the Tecnis Synergy provides a wider range of vision but is highly sensitive to corneal spherical aberration and pupil size, so thorough preoperative evaluation of corneal asphericity and functional pupil diameter is essential for IOL selection and power targeting. Full article

This work presents a biomimetic curved compound-eye imaging system (BCCEIS) engineered for extended-range depth mapping. The system is designed to emulate an apposition-type compound eye and comprises three key components: a hemispherical array of lenslets forming a curved multi-aperture imaging surface, an optical relay subsystem that transforms the curved focal plane into a flat image plane compatible with a commercial CMOS sensor, and a high-resolution CMOS detector. Comprehensive optical analysis confirms effective aberration correction, with the root-mean-square (RMS) spot radii across the field of view (FOV) remaining smaller than the radius of the Airy disk. The fabricated prototype achieves an angular resolution of 2.5 mrad within an ultra-wide 97.4° FOV. Furthermore, the system demonstrates accurate depth reconstruction within the entire FOV at distances up to approximately 2 m, exhibiting errors below 2%. Owing to its compact form, wide FOV, and robust depth-sensing performance, the BCCEIS shows strong potential as a payload for unmanned aerial vehicles in applications such as security surveillance and obstacle avoidance. Full article

The objective of this study was to compare subjective manifest refraction with wavefront-based automated refraction using iTrace (ray tracing) and LadarWave (Hartmann–Shack) in eyes implanted with two enhanced monofocal intraocular lenses (IOLs) and a standard aspheric monofocal IOL, emphasizing agreement and refractive variability across optical designs. This retrospective cohort included 84 eyes from 42 patients implanted with Tecnis Eyhance (DIB00), RayOne EMV (RAO200E), or Tecnis ZCB00 IOLs. Postoperative evaluation (1–3 months) included uncorrected and corrected distance visual acuity and subjective manifest refraction, followed by automated refraction with iTrace and LadarWave. Outcomes were sphere, cylinder, and spherical equivalent (SE). Agreement was assessed using mean signed difference, mean absolute error, root mean square error, Bland–Altman limits of agreement, proportions within clinically relevant thresholds, and vector astigmatism (J0, J45). Linear mixed-effect modeling evaluated SE differences across methods and IOL types while accounting for within-subject correlation. Subjective SE differed among IOLs (p = 0.027), with RAO200E more myopic than ZCB00 (−0.20 ± 0.32 D vs. −0.08 ± 0.44 D, p = 0.035). Automated refraction showed greater variability and poorer agreement in enhanced monofocal IOLs, particularly for cylinder and SE, with wider limits of agreement and fewer eyes within ±0.50 D compared with ZCB00. In mixed-effect contrasts (three-method repeated-measures model), iTrace and LadarWave showed a consistent myopic bias versus manifest refraction in DIB00 and RAO200E, whereas in ZCB00 the iTrace–manifest difference was not significant and LadarWave retained a significant myopic bias. Enhanced monofocal IOLs exhibit reduced agreement between wavefront-based automated and subjective manifest refraction compared with a standard aspheric monofocal IOL. Manifest refraction remains essential for postoperative assessment, and automated measurements should be interpreted as complementary, particularly in IOL designs that modify aberrations. Full article

High-precision centering alignment of the lens is crucial for ensuring the imaging quality of refractive optical systems. A multi-zone computer-generated hologram (MZ-CGH) was designed and utilized for centering a large-aperture refractive infrared lens. Different from traditional methods that use the line connecting the geometric centers of lens spheres as the optical axis for alignment, the minimization of transmitted wavefront aberrations detected via interferometry is employed as the target for lens centering. According to the structure design, the large-aperture lens is divided into a front barrel integrated with lenses 1–3, a back barrel integrated with lenses 4–5, and a separated lens 6. An MZ-CGH contains three main zones with compensation information for testing the transmitted wavefront of lenses 1–3, according to the alignment and centering sequence. The method is applied to align and analyze errors in an infrared optical system with a clear aperture of 400 mm, achieving lens decenter errors better than 5 μm. After alignment, the wavefront errors of the infrared optical system within ±7° of the field of view are better than RMS 0.07λ, with an average MTF higher than 0.5, demonstrating significant value for engineering applications. Full article

Compound meta-optics, characterized by the unprecedented complex optical architectures containing single or multiple meta-optics elements, has emerged as a powerful paradigm for overcoming the physical limitations of single-layer metasurfaces. This review systematically examines the recent progress in this burgeoning field, primarily focusing on the development of high-performance optical systems for imaging, display, sensing, and computing. We first focus on the design of compound metalens architectures that integrate metalenses with additional elements such as iris, refractive optics, or other meta-optics elements. These configurations effectively succeed in providing multiple high-quality image quality metrics simultaneously by correcting monochromatic and chromatic aberrations, expanding the field of view, enhancing overall efficiency, and so on. Thus, the compound approach enables practical applications in next-generation cameras and sensors. Furthermore, we explore the advancement of cascaded metasurfaces in the realm of wave-optics, specifically for advanced meta-holography and optical computing. These multi-layered systems facilitate complex wavefront engineering, leading to significant increases in information capacity and functionality for security and analog optical computing applications. By providing a comprehensive overview of fundamental principles, design strategies, and emerging applications, this review aims to offer a clear perspective on the pivotal role of compound meta-optics in devising and optimizing compact, multifunctional optical systems to optics engineers with a variety of professional knowledge backgrounds and techniques. Full article

Background: KMT2A partial tandem duplication (PTD) occurs in approximately 5–10% of acute myeloid leukemia (AML) cases and is associated with poor prognosis. While its cytogenetic and molecular features are well described, the immunophenotypic characteristics of AML with KMT2A-PTD remain incompletely defined. Methods: We identified 47 cases of AML with KMT2A-PTD by optical genome mapping. All cases underwent flow cytometric immunophenotypic analysis and next-generation sequencing using an 81-gene panel. Results: The cohort included 32 men and 15 women with a median age of 67 years (range, 19–87). Thirty-eight cases were de novo AML, and nine were secondary to myelodysplastic syndrome and/or myeloproliferative neoplasm. Most cases (93%) demonstrated a normal or non-complex karyotype. The most frequent mutations involved FLT3-ITD (47%), DNMT3A (43%), and RUNX1 (23%). Thirty-one cases (66%) were granulocytic, while 16 (34%) showed granulocytic and/or monocytic differentiation. Blasts uniformly expressed HLA-DR and frequently expressed CD117 (91%) and CD34 (79%). Increased expression of CD123 (74%) and CD117 (43%) and decreased expression of HLA-DR (74%) and CD38 (69%) were common. Aberrant CD25 expression was observed in 51% of cases. Increased CD123 and aberrant CD25 expression were significantly associated with FLT3-ITD mutations (both p < 0.0001) but not with other recurrent mutations. There was no correlation between FLT3-ITD mutation and expression levels of CD117, CD38 or HLA-DR (all p > 0.05). Conclusions: AML with KMT2A-PTD shows distinctive immunophenotypic features with increased CD123 and aberrant CD25 expression, both associated with FLT3-ITD. These markers may have diagnostic and therapeutic relevance in this AML subtype. Full article

Diffractive optical elements (DOEs) offer significant advantages over conventional refractive optics, particularly in non-visible spectral regions such as ultraviolet, gamma rays, and X-rays, where material limitations restrict traditional optical components. Owing to their design flexibility, DOEs enable the generation of complex beam profiles—including circular, vortex, and Airy beams—across a wide range of wavelengths. Despite their structural simplicity and compatibility with micro- and nanoscale fabrication, conventional DOEs often suffer from limited focusing efficiency, frequently requiring additional refractive lenses that introduce optical aberrations, increased system complexity, and higher cost. In this work, we present an integrated design and fabrication approach for micro-scale diffractive optical elements capable of achieving high focusing performance without reliance on supplementary optical components. A machine learning-based decision tree method is employed to generate optimized writing paths, which are subsequently fabricated using direct laser lithography. The proposed integrated DOE structures enable efficient focusing of multiple customized beam profiles within a compact and standalone optical element. This approach improves optical efficiency while maintaining low fabrication cost and system simplicity. The demonstrated integrated micro-DOEs provide a scalable and versatile platform for advanced beam shaping and focusing applications in photonics, particularly where compactness and performance are critical. Full article

Background and Objectives: Keratoconus (KC) is a progressive ectatic corneal disease that can cause irregular astigmatism and visual impairment. To describe the demographic and clinical profile of KC patients attending major eye care centers in Riyadh City, Saudi Arabia, and to explore associations with laterality, disease severity, and management patterns. Materials and Methods: This multi-center hospital-based cross-sectional study enrolled consecutive patients with a confirmed diagnosis of KC (new or follow-up) presenting between April 2022 and April 2023. All participants underwent standardized ophthalmic assessment and Scheimpflug tomography (Pentacam). Disease severity was categorized as early, moderate, or advanced using Pentacam-derived keratoconus staging, and ocular parameters (refraction, keratometry, pachymetry, and higher-order aberrations) were compared across severity categories. Results: A total of 157 patients (264 eyes) were included (mean age 31.8 years; 56.7% female), with bilateral KC in 68.2%. Eye rubbing (67.8%) and allergic symptoms (61.7%) were common. Keratometric indices and higher-order aberrations differed significantly by severity grade (p < 0.001). Management patterns differed by sex and laterality, with corneal cross-linking and glasses reported more frequently in males, and soft contact lens use concentrated among bilateral cases. Conclusions: In this hospital-based Riyadh sample, KC was often associated with eye rubbing and allergic symptoms and showed clear stage-dependent worsening of tomographic indices and optical quality. These findings support early detection and targeted counseling on modifiable behaviors, while population-based studies with non-diseased comparators are needed to quantify incidence and prevalence in Riyadh. Full article

Presbyopia-correcting IOLs have revolutionized cataract surgery by enabling functional vision across multiple focal distances, thereby reducing dependence on spectacles. These lenses—ranging from multifocal to extended depth-of-focus (EDOF) and hybrid designs—incorporate advanced optical technologies to address the limitations of traditional monofocal IOLs. Despite their clinical promise, patient satisfaction remains variable, with a substantial subset experiencing postoperative visual discomfort. This review provides a comprehensive overview of presbyopia-correcting IOL technologies, detailing their optical principles, design evolution, and clinical performance. It further analyzes the multifactorial causes of postoperative dissatisfaction, which include optical phenomena such as glare, halos, and reduced contrast sensitivity; ocular comorbidities like dry eye disease, corneal irregular astigmatism, glaucoma, and macular pathology; and surgical variables including IOL centration, pupil size, and biometry accuracy. Additionally, non-physiological factors—such as patient expectations, lifestyle demands, and psychological disposition—play a critical role in perceived outcomes. To address these challenges, the review explores evidence-based strategies for improving satisfaction. These include rigorous preoperative screening for ocular surface disease and aberrations, personalized lens selection based on anatomical and functional criteria, and thorough patient counseling to align expectations with achievable results. Emerging IOL designs that blend multifocal and EDOF features offer promising avenues for minimizing visual disturbances while preserving range of vision. By integrating optical innovation with individualized clinical care, ophthalmologists can enhance postoperative outcomes and optimize real-world satisfaction with presbyopia-correcting IOLs. Full article

Atmospheric turbulence significantly degrades the performance of High Energy Laser (HEL) systems by distorting the laser wavefront as it propagates through the atmosphere. Conventional correction techniques rely on Adaptive Optics (AO), which preserve beam quality at the object. However, AO systems require wavefront sensors, such as Shack–Hartmann, and a reference beam, increasing system complexity and cost. This work presents a Deep Learning (DL)-based wavefront sensing approach that operates directly on scene imagery, thereby eliminating the need for dedicated wavefront sensors and a reference beam. A DL model was trained to predict wavefront distortions, represented by Zernike coefficients, from aberrated imagery of the Reaper Unmanned Aerial Vehicle (UAV). Reaper imagery utilized in training was aberrated at different levels of turbulence, $D/r_0$, with $D=30$ cm being the aperture diameter of a telescope capturing the object scene and $r_0=3, 5, 7$ cm the Fried parameter that defines weak turbulence for higher values and strong turbulence for lower values. The proposed model, trained across all these turbulence levels, outperformed models trained on a single level by providing superior accuracy and offering practical advantages for deployment. The model also demonstrated strong generalization capabilities for two practical scenarios: (a) Reaper imagery with turbulence levels beyond the training range, and (b) Mongoose UAV imagery not included in the training set. The model predicts turbulence accurately in both cases. The results confirm that if the model is trained for a UAV model for a certain turbulence level, it provides accurate predictions for turbulence levels outside its training range and for other UAV aberrated images. Full article