Stereoscopic depth perception through foliage.

Both humans and computational methods struggle to discriminate the depths of objects hidden beneath foliage. However, such discrimination becomes feasible when we combine computational optical synthetic aperture sensing with the human ability to fuse stereoscopic images. For object identification tasks, as required in search and rescue, wildlife observation, surveillance, and early wildfire detection, depth assists in differentiating true from false findings, such as people, animals, or vehicles vs. sun-heated patches at the ground level or in the tree crowns, or ground fires vs. tree trunks. We used video captured by a drone above dense woodland to test users' ability to discriminate depth. We found that this is impossible when viewing monoscopic video and relying on motion parallax. The same was true with stereoscopic video because of the occlusions caused by foliage. However, when synthetic aperture sensing was used to reduce occlusions and disparity-scaled stereoscopic video was presented, whereas computational (stereoscopic matching) methods were unsuccessful, human observers successfully discriminated depth. This shows the potential of systems which exploit the synergy between computational methods and human vision to perform tasks that neither can perform alone.

X-ray ghost imaging with a specially developed beam splitter.

X-ray ghost imaging with a crystal beam splitter has advantages in highly efficient imaging due to the simultaneous acquisition of signals from both the object beam and reference beam. However, beam splitting with a large field of view, uniform distribution and high correlation has been a great challenge up to now. Therefore, a dedicated beam splitter has been developed by optimizing the optical layout of a synchrotron radiation beamline and the fabrication process of a Laue crystal. A large field of view, consistent size, uniform intensity distribution and high correlation were obtained simultaneously for the two split beams. Modulated by a piece of copper foam upstream of the splitter, a correlation of 92% between the speckle fields of the object and reference beam and a Glauber function of 1.25 were achieved. Taking advantage of synthetic aperture X-ray ghost imaging (SAXGI), a circuit board of size 880 × 330 pixels was successfully imaged with high fidelity. In addition, even though 16 measurements corresponding to a sampling rate of 1% in SAXGI were used for image reconstruction, the skeleton structure of the circuit board can still be determined. In conclusion, the specially developed beam splitter is applicable for the efficient implementation of X-ray ghost imaging.

Designing hollow-core PCF sensors for high-performance terahertz detection of NaCN and KCN.

Cyanide is very poisonous and raises environmental problems because of its industrial application and potential as a terrorist weapon. Given CN's toxicity and possible hazard to people, an effective and adaptive detection approach is needed. This specification suggests using a PCF to build a terahertz Hexagonal Core and Curved rectangular air holes sensor to detect NaCN and KCN. The recently created PCF analysis, which was promptly delivered, reveals an RS concentration of 99.62 % for NaCN and a maximum concentration of KCN is 99.08 %. In addition, we analyzed the Confinement Loss (CL) at a value of 5.88 × 10-09 dB/m and 2.07 × 10-05 dB/m, as well as EML at values of 0.0020 cm-1 and 0.0026 cm-1, accordingly, about these hazardous substances. The designed detector can identify NaCN and KCN at low concentrations even with small RI shifts due to its high sensitivity. Real-time NaCN and KCN detection and monitoring through nerve reflexes is essential for life-threatening conditions. It can selectively work in NaCN and KCN, ensuring accurate detection even in complex chemical compositions. Additionally, its tiny size allows for emergency use.

The Latest Developments in Spaceborne High-Resolution Wide-Swath SAR Systems and Imaging Methods.

Azimuth resolution and swath width are two crucial parameters in spaceborne synthetic aperture radar (SAR) systems. However, it is difficult for conventional spaceborne SAR to simultaneously achieve high-resolution wide-swath (HRWS) due to the minimum antenna area constraint. To mitigate this limitation, some representative HRWS SAR imaging techniques have been investigated, e.g., the azimuth multichannel technique, digital beamforming (DBF) technique, and pulse repetition interval (PRI) variation technique. This paper focus on a comprehensive review of the three techniques with respect to their latest developments. First, some key parameters of HRWS SAR are presented and analyzed to help the reader establish the general concept of SAR. Second, three techniques are introduced in detail, roughly following a simple-to-complex approach, i.e., start with the basic concept, then move to the core principles and classic technical details, and finally report the technical challenges and corresponding solutions. Third, some in-depth insights on the comparison among the three techniques are given. The purpose of this paper is to provide a review and brief perspective on the development of HRWS SAR.

Accurate Low Complexity Quadrature Angular Diversity Aperture Receiver for Visible Light Positioning.

Despite the many potential applications of an accurate indoor positioning system (IPS), no universal, readily available system exists. Much of the IPS research to date has been based on the use of radio transmitters as positioning beacons. Visible light positioning (VLP) instead uses LED lights as beacons. Either cameras or photodiodes (PDs) can be used as VLP receivers, and position estimates are usually based on either the angle of arrival (AOA) or the strength of the received signal. Research on the use of AOA with photodiode receivers has so far been limited by the lack of a suitable compact receiver. The quadrature angular diversity aperture receiver (QADA) can fill this gap. In this paper, we describe a new QADA design that uses only three readily available parts: a quadrant photodiode, a 3D-printed aperture, and a programmable system on a chip (PSoC). Extensive experimental results demonstrate that this design provides accurate AOA estimates within a room-sized test chamber. The flexibility and programmability of the PSoC mean that other sensors can be supported by the same PSoC. This has the potential to allow the AOA estimates from the QADA to be combined with information from other sensors to form future powerful sensor-fusion systems requiring only one beacon.

Enhancing Bioluminescence Imaging of Cultured Tissue Explants Using Optical Telecompression.

Long-term observation of single-cell oscillations within tissue networks is now possible by combining bioluminescence reporters with stable tissue explant culture techniques. This method is particularly effective in revealing the network dynamics in systems with slow oscillations, such as circadian clocks. However, the low intensity of luciferase-based bioluminescence requires signal amplification using specialized cameras (e.g., I-CCDs and EM-CCDs) and prolonged exposure times, increasing baseline noise and reducing temporal resolution. To address this limitation, we implemented a cost-effective optical enhancement technique called telecompression, first used in astrophotography and now commonly used in digital photography. By combining a high numerical aperture objective lens with a magnification-reducing relay lens, we significantly increased the collection efficiency of the bioluminescence signal without raising the baseline CCD noise. This method allows for shorter exposure times in time-lapse imaging, enhancing temporal resolution and enabling more precise period estimations. Our implementation demonstrates the feasibility of telecompression for enhancing bioluminescence imaging for the tissue-level network observation of circadian clocks.

A Novel Topology of a 3 × 3 Series Phased Array Antenna with Aperture-Coupled Feeding.

This paper presents a novel 3 × 3 phased array antenna optimized for 4 GHz operation, achieving a realized gain of 13.2 dBi and enabling 30-degree beam steering with a minimal capacitance variation of 1.5 pF. The design features a series aperture-coupled feeding mechanism that not only reduces the antenna's size but also simplifies the fabrication process, making the device both cost-effective and compact. Integrating cost-efficient quadrature-hybrid phase shifters and novel power splitters with cascaded quadrature hybrids ensures uniform power distribution and precise beam steering. The innovative use of these components addresses common challenges in phased array systems, such as space constraints, high costs, and complex power distribution.

A Novel Methodology for GB-SAR Estimating Parameters of the Atmospheric Phase Correction Model Based on Maximum Likelihood Estimation and the Gauss-Newton Algorithm.

Atmospheric phase error is the main factor affecting the accuracy of ground-based synthetic aperture radar (GB-SAR). The atmospheric phase screen (APS) may be very complicated, so the atmospheric phase correction (APC) model is very important; in particular, the parameters to be estimated in the model are the key to improving the accuracy of APC. However, the conventional APC method first performs phase unwrapping and then removes the APS based on the least-squares method (LSM), and the general phase unwrapping method is prone to introducing unwrapping error. In particular, the LSM is difficult to apply directly due to the phase wrapping of permanent scatterers (PSs). Therefore, a novel methodology for estimating parameters of the APC model based on the maximum likelihood estimation (MLE) and the Gauss-Newton algorithm is proposed in this paper, which first introduces the MLE method to provide a suitable objective function for the parameter estimation of nonlinear far-end and near-end correction models. Then, based on the Gauss-Newton algorithm, the parameters of the objective function are iteratively estimated with suitable initial values, and the Matthews and Davies algorithm is used to optimize the Gauss-Newton algorithm to improve the accuracy of parameter estimation. Finally, the parameter estimation performance is evaluated based on Monte Carlo simulation experiments. The method proposed in this paper experimentally verifies the feasibility and superiority, which avoids phase unwrapping processing unlike the conventional method.

High resolution ultrasonic imaging of extended targets via combined match field and time delay beamforming.

Ultrasound imaging using an active sensing array has been extensively studied in both time domain and frequency domain. Subspace decomposition methods in match field beamforming such as the multiple signal classification (MUSIC) algorithm can achieve subwavelength resolution of distinct point scatterers. However, when the size of the target is on the order of one wavelength or larger, the MUSIC type algorithms suffer from poor performance due to a tangled eigen structure. This paper proposes an adaptive match field beamformer that does not require subspace decomposition to achieve high resolution imaging of extended targets. Specifically, the broadband coherent white noise constraint (C-WNC) algorithm is utilized to achieve high focusing ability of extended targets by exploiting the cross-frequency coherence in an active sensing scheme. The dynamic range bias in the adaptive beamformer benefits the C-WNC algorithm to achieve high contrast regardless of the SNR. Both simulations and experiments show that the C-WNC images retain their resolution cells on the tips of the extended target with sizes ranging from a wavelength to sizes as large as the physical aperture width. A robust imaging scheme is then proposed to obtain high quality images by combining C-WNC images with a statistically stable delay-multiply-and-sum (DMAS) algorithm to create high-contrast and high-resolution images of extended targets in both azimuth and axial range directions.

Multi-source machine learning and spaceborne remote sensing data accurately predict three-dimensional soil moisture in an in-service uranium disposal cell.

One reason arid and semi-arid environments have been used to store waste is due to low groundwater recharge, presumably limiting the potential for meteoric water to mobilize and transport contaminants into groundwater. The U.S. Department of Energy Office of Legacy Management (LM) is evaluating selected uranium mill tailings disposal cell covers to be managed as evapotranspiration (ET) covers, where vegetation is used to naturally remove water from the cover profile via transpiration, further reducing deep percolation. An important parameter in monitoring the performance of ET covers is soil moisture (SM). If SM is too high, water may drain into tailings material, potentially transporting contaminants into groundwater; if SM is too low, radon flux may increase through the cover. However, monitoring SM via traditional instrumentation is invasive, expensive, and may fail to account for spatial heterogeneity, especially over vegetated disposal cells. Here we investigated the potential for non-invasive SM monitoring using radar remote sensing and other geospatial data to see if this approach could provide a practical, accurate, and spatially comprehensive tool to monitor SM. We used theoretical simulations to analyze the sensitivity of multi-frequency radar backscatter to SM at different depths of a field-scale (3 ha) drainage lysimeter embedded within an in-service LM disposal cell. We then evaluated a shallow and deep form of machine learning (ML) using Google Earth Engine to integrate multi-source observations and estimate the SM profile across six soil layers from depths of 0-2 m. The ML models were trained using in situ SM measurements from 2019 and validated using data from 2014 to 2018 and 2020-2021. Model predictors included backscatter observations from satellite synthetic aperture radar, vegetation, temperature products from optical infrared sensors, and accumulated, gridded rainfall data. The radar simulations confirmed that the lower frequencies (L- and P-band) and smaller incidence angles show better sensitivity to deeper soil layers and an overall larger SM dynamic range relative to the higher frequencies (C- and X-band). The ML models produced accurate SM estimates throughout the soil profile (r values from 0.75 to 0.94; RMSE = 0.003-0.017 cm3/cm3; bias = 0.00 cm3/cm3), with the simpler shallow-learning approach outperforming a selected deep-learning model. The ML models we developed provide an accurate, cost-effective tool for monitoring SM within ET covers that could be applied to other vegetated disposal cell covers, potentially including those with rock-armored covers.

Congenital Nasal Pyriform Aperture Stenosis and the Significance of McGovern Nipple.

Congenital nasal pyriform aperture stenosis (CNPAS) is a rare but potentially life-threatening cause of upper airway obstruction in infants. It was first described in 1988 and 1989 in the radiology and otolaryngology literature. Congenital airway obstruction affects up to 1 in 5,000 infants, and many of these obstructions result from choanal atresia. CNPAS is estimated to occur 1 in 25,000 live births. This case report describes a neonate with acute respiratory distress and obstructive breathing pattern relieved by opening her oral airway and maintained with the McGovern nipple decreasing ventilator days during hospitalization with viral bronchiolitis.

Lightweight deep neural network for radio frequency interference detection and segmentation in synthetic aperture radar.

Radio frequency interference (RFI) poses challenges in the analysis of synthetic aperture radar (SAR) images. Existing RFI suppression systems rely on prior knowledge of the presence of RFI. This paper proposes a lightweight neural network-based algorithm for detecting and segmenting RFI (LDNet) in the time-frequency domain. The network accurately delineates RFI pixel regions in time-frequency spectrograms. To mitigate the impact on the operational speed of the entire RFI suppression system, lightweight modules and pruning operations are introduced. Compared to threshold-based RFI detection algorithms, deep learning-based segmentation networks, and AC-UNet specifically designed for RFI detection, LDNet achieves improvements in mean intersection over union (MIoU) by 24.56%, 13.29%, and 7.54%, respectively.Furthermore, LDNet reduces model size by 99.03% and inference latency by 24.53% compared to AC-UNet.

Congenital Pyriform Aperture Stenosis: Not All Patients Require Open Repair.

OBJECTIVE: Evaluate the management options for congenital nasal pyriform aperture stenosis (CNPAS). STUDY DESIGN: Case series. SETTING: Tertiary referral children's hospital. METHODS: The medical records of CNPAS patients managed from January 2015 to 2023 were reviewed for medical history, management, and outcomes. RESULTS: Fifteen patients met inclusion criteria. Six patients (40.0%) had a central mega incisor and 4 (26.7%) had holoprosencephaly. Three (20%) patients were managed with medications alone. Mean PA width was similar between patients managed medically versus those managed surgically (mean width 6.2 ± 0.15 mm vs 6.1 ± 0.38 mm). Median age at first procedure was 50 (range 8-263) days. Seven (46.7%) underwent an initial balloon nasal dilation and 5 (33.3%) underwent an open sublabial repair. Operative time was lower in the balloon dilation group (mean 27 vs 104 minutes). Five patients had a single balloon dilation and 2 required revision procedures: 1 underwent a second balloon dilation, and 1 patient underwent a subsequent open sublabial procedure. Four patients with an initial open sublabial approach returned to the operating room for nasal balloon dilation or debridement due to nasal synechiae. CONCLUSION: There has been general shift towards minimally invasive surgery. In our series, 8 (53.3%) patients were managed successfully with medical therapy or a single nasal balloon dilation procedure. Of those who underwent an open surgical repair, most (4/5) required a revision procedure due to synechiae. Given the relative success and lower operative time of balloon dilation, this option should be considered in the management algorithm for CNPAS.

Congenital bilateral nasal obstruction in neonate: Case report with review of literature for congenital nasal pyriform aperture stenosis (CNPAS) and differential diagnosis and management.

Congenital nasal pyriform aperture stenosis is a newly defined clinical entity that causes nasal airway obstruction in neonates due to the narrowing of the pyriform aperture, which is the narrowest and most anterior portion of the nasal airway. As newborns are obligate nasal breathers except when crying, a child with bilateral nasal pyriform aperture obstruction presents as an acute airway emergency, resulting in apnea and cyanosis. This entity should be kept in the differential diagnosis of any neonate or infant presenting with signs and symptoms of upper airway obstruction.

The Small Auxin-Up RNA 50 (SAUR50) Gene from Ammopiptanthus nanus Negatively Regulates Drought Tolerance.

Drought stress is a primary abiotic stress that causes significant losses to forestry and agricultural production. Therefore, exploring drought-responsive genes and their regulatory mechanism is crucial for plant molecular breeding for forestry and agriculture production safety. Small auxin-up RNA (SAUR) proteins are essential in plant growth and development but show functional diversity in stress response. In this study, the transcriptome sequencing data of Ammopiptanthus nanus seedlings revealed that the expression of AnSAUR50 was continuously downregulated under drought stress. Hence, the AnSAUR50 gene was cloned and functionally analyzed in drought response. The results showed that the coding sequence of AnSAUR50 was 315 bp in length and encoded 104 amino acids. The AnSAUR50 protein showed high conservation, possessed a SAUR-specific domain, and localized in the nucleus and cell membrane. The heterologous expression of the AnSAUR50 gene enhanced the drought sensitivity of the transgenic Arabidopsis with a lower survival rate, biomass, and higher malondialdehyde content and relative electrolyte leakage. Moreover, transgenic plants showed shorter root lengths and bigger stomatal apertures, resulting in facilitating water loss under drought stress. The study indicates that AnSAUR50 negatively regulates drought tolerance by inhibiting root growth and stomatal closure, which provides insights into the underlying function and regulatory mechanism of SAURs in plant stress response.

Structural insight into the Arabidopsis vacuolar anion channel ALMT9 shows clade specificity.

The Arabidopsis thaliana aluminum-activated malate transporter 9 (AtALMT9) functions as a vacuolar chloride channel that regulates the stomatal aperture. Here, we present the cryoelectron microscopy (cryo-EM) structures of AtALMT9 in three distinct states. AtALMT9 forms a dimer, and the pore is lined with four positively charged rings. The apo-AtALMT9 state shows a putative endogenous citrate obstructing the pore, where two W120 constriction residues enclose a gate with a pore radius of approximately 1.8 Å, representing an open state. Interestingly, channel closure is solely controlled by W120. Compared to wild-type plants, the W120A mutant exhibits more sensitivity to drought stress and is unable to restore the visual phenotype on leaves upon water recovery, reflecting persistent stomatal opening. Furthermore, notable variations are noted in channel gating and substrate recognition of Glycine max ALMT12, AtALMT9, and AtALMT1. In summary, our investigation enhances comprehension of the interplay between structure and function within the ALMT family.

Machine Learning Algorithms for Sex Classification by Using Variables of Orbital Structures: A Computed Tomography Study / Algoritmos de Aprendizaje Automático para la Clasificación del Sexo Mediante el Uso de Variables de Estructuras Orbitales: Un Estudio de Tomografía Computarizada

SUMMARY: Since machine learning algorithms give more reliable results, they have been used in the field of health in recent years. The orbital variables give very successful results in classifying sex correctly. This research has focused on sex determination using certain variables obtained from the orbital images of the computerized tomography (CT) by using machine learning algorithms (ML). In this study 12 variables determined on 600 orbital images of 300 individuals (150 men and 150 women) were tested with different ML. Decision tree (DT), K-Nearest Neighbour (KNN), Logistic Regression (LR), Random Forest (RF), Linear Discriminant Analysis (LDA), and Naive Bayes (NB) algorithms of ML were used for unsupervised learning. Statistical analyses of the variables were conducted with Minitab® 21.2 (64-bit) program. ACC rate of NB, DT, KNN, and LR algorithms was found as % 83 while the ACC rate of LDA and RFC algorithms was determined as % 85. According to Shap analysis, the variable with the highest degree of effect was found as BOW. The study has determined the sex with high accuracy at the ratios of 0.83 and 0.85 through using the variables of the orbital CT images, and the related morphometric data of the population under question was acquired, emphasizing the racial variation.

Dado que los algoritmos de aprendizaje automático dan resultados más fiables, en los últimos años han sido utilizados en el campo de la salud. Las variables orbitales dan resultados muy exitosos a la hora de clasificar correctamente el sexo. Esta investigación se ha centrado en la determinación del sexo utilizando determinadas variables obtenidas a partir de las imágenes orbitales de la tomografía computarizada (TC) mediante el uso de algoritmos de aprendizaje automático (AA). En este estudio se probaron 12 variables determinadas en 600 imágenes orbitales de 300 individuos (150 hombres y 150 mujeres) con diferentes AA. Se utilizaron algoritmos de AA de árbol de decisión (DT), K-Nearest Neighbour, regresión logística (RL), Random Forest (RF), análisis discriminante lineal (ADL) y Naive Bayes (NB) para el aprendizaje no supervisado. Los análisis estadísticos de las variables se realizaron con el programa Minitab® 21.2 (64 bits). La tasa de ACC de los algoritmos NB, DT, KNN y RL se encontró en % 83, mientras que la tasa de ACC de los algoritmos ADL y RFC se determinó en % 85. Según el análisis de Sharp, la variable con el mayor grado de efecto se encontró como BOW. El estudio determinó el sexo con alta precisión en las proporciones de 0,83 y 0,85 mediante el uso de las variables de las imágenes de TC orbitales, y se adquirieron los datos morfométricos relacionados de la población en cuestión, enfatizando la variación racial.

The surface deformation of permafrost and active layer thickness in the upper reaches of the Black River basin, revealed by InSAR observations and independent component analysis.

The Heihe River Basin, located in the northeastern part of the Qinghai-Tibetan Plateau, is part of the perennial permafrost belt of the Qilian Mountains. Recent observations indicate ongoing permafrost degradation in this region. This study utilizes data from 255 observations provided by Sentinel-1 satellites, MODIS Land Surface Temperature, SMAP-L4 soil moisture data, GNSS measurements, and in situ measurement. We introduced Variational Bayesian independent Component Analysis (VB-ICA) in multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) processing to investigate the spatial-temporal characteristics of surface deformation and permafrost active layer thickness (ALT) variations. The analysis demonstrates strong agreement with borehole data and offers improvements over traditional methodologies. The maximum value of ALT in the basin is found to be 5.7 m. VB-ICA effectively delineates seasonal deformations related to the freeze-thaw cycles, with a peak seasonal deformation amplitude of 60 mm. Moreover, the seasonal permafrost's lower boundary reaches an elevation of 3700 m, revealing that permafrost is experiencing widespread degradation and associated soil erosion in the high elevation region of The Heihe River Basin. The paper also explores the efficacy of reference point selection and baseline network establishment for employing the InSAR method in monitoring freeze-thaw deformations. The study underscores the InSAR method's adaptability and its importance for interpreting permafrost deformation and related parameters.

A dosimetrically motivated pathfinding approach for non-isocentric dynamic trajectory radiotherapy.

Objective.Non-isocentric dynamic trajectory radiotherapy (DTRT) involves dynamic table translations in synchrony with intensity modulation and dynamic gantry, table, and/or collimator rotation. This work aims to develop and evaluate a novel dosimetrically motivated path determination technique for non-isocentric DTRT.Approach.The path determination considers all available beam directions, given on a user-specified grid of gantry angle, table angle, and longitudinal, vertical, and lateral table position. Additionally, the source-to-target distance of all beam directions can be extended by moving the table away from the gantry along the central beam axis to increase the collision-free space. The path determination uses a column generation algorithm to iteratively add beam directions to paths until a user-defined total path length is reached. A subsequent direct aperture optimization of the intensity modulation along the paths creates deliverable plans. Non-isocentric DTRT plans using the path determination and using a manual path setup were created for a craniospinal and a spinal irradiation case. Furthermore, VMAT, isocentric DTRT, and non-isocentric DTRT plans are created for a breast, head and neck (H&N), and esophagus case. Additionally, a HyperArc plan is created for the H&N case. The plans are compared in terms of the dosimetric treatment plan quality and estimated delivery time.Main results.For the craniospinal and spinal irradiation case, using path determination results in dose distributions with improved conformity but a slightly worse target homogeneity compared to manual path setup. The non-isocentric DTRT plans maintained target coverage while reducing the mean dose to organs-at-risk on average by 1.7 Gy (breast), 1.0 Gy (H&N), and 1.6 Gy (esophagus) compared to the VMAT plans and by 0.8 Gy (breast), 0.6 Gy (H&N), and 0.8 Gy (esophagus) compared to the isocentric DTRT plans.Significance.A general dosimetrically motivated path determination applicable to non-isocentric DTRT plans is successfully developed, further advancing the treatment planning for non-isocentric DTRT.

Incorrectly Focused Neodymium:Yttrium-Aluminum-Garnet (Nd:YAG) Laser Beam Leads to Massive Destructive Effects in Small-Aperture (Pinhole) Intraocular Lenses.

INTRODUCTION: Pinhole intraocular lenses (IOLs) were developed to improve reading by compensating for loss of accommodative function. The IC-8® Apthera™ is a small-aperture presbyopia-correcting IOL that combines the proven principle of small-aperture optics with an aspheric monofocal lens to deliver a continuous range of vision for patients with cataracts from distance to near vision. Posterior capsule opacification is the most common sequela after cataract surgery. It is effectively treated by laser capsulotomy. However, if the laser beam is incorrectly focused, the IOL can be permanently damaged (pits/shots). METHODS: In this experimental study, yttrium-aluminum-garnet (YAG) pits were purposefully created. Defects were analyzed and compared between the periphery of the ring in the clear area of the hydrophobic acrylic lens and at the carbon black (CB)-polyvinylidene fluoride (PVDF) filtering component (FilterRing™) of the pinhole lens. All defects were made using identical settings/energy levels (2.6 mJ). The damage induced to the IC-8® Apthera™ IOL was examined by low-magnification images, light microscopy, scanning electron microscopy, and micro-computed tomography (micro-CT). RESULTS: YAG defects in the carbon black filter ring were much more severe than those in the clear zone due to the high absorption of the carbon black. Massive defects and destruction of the lens with tearing out of fragments and particles were observed. The missing volume calculated from the micro-CT reconstruction was 0.266 mm3, which is 1.6% of the entire IOL volume, or more than 1000 times the volume damaged in the largest shot in the periphery. CONCLUSION: Based on the results, we highly recommend using the lowest possible energy levels, posterior offset setting, and circular pattern for maximum safety when performing laser capsulotomy with pinhole implants. Care should be taken to avoid creating irreversible iatrogenic defects that may affect overall quality. The safest area for performing capsulotomy seems to be the periphery of the ring segment. Video available for this article.