Aperture Shape Research Articles

Effects of Aperture Shape on Absorption Property of Acoustic Metamaterial of Parallel-Connection Helmholtz Resonator.

A Helmholtz resonator (HR) with an embedded aperture is an effective acoustic metamaterial for noise reduction in the low-frequency range. Its sound absorption property is significantly affected by the aperture shape. Sound absorption properties of HRs with the embedded aperture for various tangent sectional shapes were studied by a two-dimensional acoustic finite element simulation. The sequence of resonance frequency from low to high was olive, common trapeziform, reverse trapeziform, dumbbell and rectangle. Meanwhile, those HRs for various cross-sectional shapes were investigated by a three-dimensional acoustic finite element simulation. The sequence of resonance frequency from low to high were round, regular hexagon, square, regular triangle and regular pentagon. Moreover, the reason for these phenomena was analyzed by the distributions of sound pressure, acoustic velocity and temperature. Furthermore, on the basement of the optimum tangent and cross-sectional shape, the sound absorption property of parallel-connection Helmholtz resonators was optimized. The experimental sample with optimal parameters was fabricated, and its average sound absorption coefficient reached 0.7821 in 500-820 Hz with a limited thickness of 30 mm. The research achievements proved the significance of aperture shape, which provided guidance for the development of sound absorbers in the low-frequency range.

FluxCT: A Web Tool for Identifying Contaminating Flux in Kepler and TESS Target Pixel Files

We announce FluxCT, a web tool for identifying contaminating flux in Kepler and TESS target pixel files due to secondary visual sources. We demonstrate the usage of this tool and discuss the benefits of this tool over a simple Gaia radius search. FluxCT focuses on clarity and simplicity, where the only input needed from the user is a KIC or TIC ID. By more appropriately accounting for the actual shape of the photometric pixel apertures, FluxCT can produce much more accurate estimates of contaminating flux than simple radial cone searches.

Clinical experience on patient-specific quality assurance for CBCT-based online adaptive treatment plan.

Ethos CBCT-based adaptive radiotherapy (ART) system can generate an online adaptive plan by re-optimizing the initial reference plan based on the patient anatomy at the treatment. The optimization process is fully automated without any room for human intervention. Due to the change in anatomy, the ART plan can be significantly different from the initial plan in terms of plan parameters such as the aperture shapes and number of monitor units (MUs). In this study, we investigated the feasibility of using calculation-based patient specific QA for ART plans in conjunction with measurement-based and calculation-based QA for initial plans to establish an action level for the online ART patient-specific QA. A cohort of 98 cases treated on CBCT-based ART system were collected for this study. We performed measurement-based QA using ArcCheck and calculation-based QA using Mobius for both the initial plan and the ART plan for analysis. For online the ART plan, Mobius calculation was conducted prior to the delivery, while ArcCheck measurement was delivered on the same day after the treatment. We first investigated the modulation factors (MFs) and MU numbers of the initial plans and ART plans, respectively. The γ passing rates of initial and ART plan QA were analyzed. Then action limits were derived for QA calculation and measurement for both initial and online ART plans, respectively, from 30 randomly selected patient cases, and were evaluated using the other 68 patient cases. The difference in MF between initial plan and ART-plan was 12.9% ± 12.7% which demonstrates their significant difference in plan parameters. Based on the patient QA results, pre-treatment calculation and measurement results are generally well aligned with ArcCheck measurement results for online ART plans, illustrating their feasibility as an indicator of failure in online ART QA measurements. Furthermore, using 30 randomly selected patient cases, the γ analysis action limit derived for initial plans and ART plans are 89.6% and 90.4% in ArcCheck QA (2%/2mm)andare 92.4% and 93.6% in Mobius QA(3%/2mm),respectively.According to the calculated action limits, the ArcCheck measurements for all the initial and ART plans passed QA successfully while the Mobius calculation action limits flagged seven and four failure cases respectively for initial plans and ART plans, respectively. An ART plan can be substantially different from the initial plan, and therefore a separate session of ART plan QA is needed to ensure treatment safety and quality. The pre-treatment QA calculation via Mobius can serve as a reliable indicator of failure in online ART plan QA. However, given that Ethos ART system is still relatively new, ArcCheck measurement of initial plan is still in practice. It may be skipped as we gain more experience and have better understanding of the system.

Rhizobium induced modulation of growth and photosynthetic efficiency of Lens culinaris Medik. grown on fly ash amended soil by antioxidants regulation.

Rhizobium leguminosarum is a rhizospheres' nitrogen fixing microbe that improves plant growth and productivity by releasing sufficient nutrient sources from the root, by biological nitrogen fixation, solubilization of phosphorous, acquisition of iron, and enhancement of antioxidant activity in plants. On this account, a greenhouse experiment was carried out to assess the feasibility of growing lentil (Lens culinaris Medik.) on fly ash (FA) amended soil (0%, 10%, 20%, and 30%) in combination with R. leguminosarum inoculation. The data was recorded at 45day after sowing to evaluate the plant growth characteristics, photosynthetic variables (total chlorophyll and carotenoid pigments, carbonic anhydrase activity, nitrate reductase activity), damage markers (ROS, MDA, and cell viability), and defensive factors (proline and antioxidants). Among the FA-proportions tested, 20% proved most favorable in all the mentioned attributes while 30% concentration had negative repercussions on all the variables. Rhizobium inoculation had synergistic effect on all the concentrations being maximum on 20% FA. Thus, Rhizobium and 20% FA caused a significant increase on growth characteristics, photosynthetic pigments; stomatal behavior (aperture shape, size, and frequency of stomata); and activity of CA and NR, and cell viability. Application of Rhizobium on 20% FA was corroborated with decline in MDA and ROS contents and a coordinated enhancement of the activity of SOD, CAT, and POX. Therefore, 20% FA with flyash-tolerant strain of Rhizobium in Lens culinaris may be utilized as an integrated approach towards sustainable agriculture and an impulse of management of fly-ash.

Deep learning-based prediction of deliverable adaptive plans for MR-guided adaptive radiotherapy: A feasibility study.

Fast and automated plan generation is desirable in radiation therapy (RT), in particular, for MR-guided online adaptive RT (MRgOART) or real-time (intrafractional) adaptive RT (MRgRART), to reduce replanning time. The purpose of this study is to investigate the feasibility of using deep learning to quickly predict deliverable adaptive plans based on a target dose distribution for MRgOART/MRgRART. A conditional generative adversarial network (cGAN) was trained to predict the MLC leaf sequence corresponding to a target dose distribution based on reference plan created prior to MRgOART using a 1.5T MR-Linac. The training dataset included 50 ground truth dose distributions and corresponding beam parameters (aperture shapes and weights) created during MRgOART for 10 pancreatic cancer patients (each with five fractions). The model input was the dose distribution from each individual beam and the output was the predicted corresponding field segments with specific shape and weight. Patient-based leave-one-out-cross-validation was employed and for each model trained, four (44 training beams) out of five fractionated plans of the left-out patient were set aside for testing purposes. We deliberately kept a single fractionated plan in the training dataset so that the model could learn to replan the patient based on a prior plan. The model performance was evaluated by calculating the gamma passing rate of the ground truth dose vs. the dose from the predicted adaptive plan and calculating max and mean dose metrics. The average gamma passing rate (95%, 3mm/3%) among 10 test cases was 88%. In general, we observed 95% of the prescription dose to PTV achieved with an average 7.6% increase of max and mean dose, respectively, to OARs for predicted replans. Complete adaptive plans were predicted in ≤20 s using a GTX 1660TI GPU. We have proposed and demonstrated a deep learning method to generate adaptive plans automatically and rapidly for MRgOART. With further developments using large datasets and the inclusion of patient contours, the method may be implemented to accelerate MRgOART process or even to facilitate MRgRART.

Statically and dynamically flexible hydrogen-bonded frameworks based on 4,5,9,10-tetrakis(4-carboxyphenyl)pyrene.

Aperture shape and size of flexible hydrogen-bonded organic frameworks (HOF) were statically modulated using various aromatic solvents, and dynamically changed by desorption and adsorption of the solvent molecules.

A New Methodology to Assess Spatial Response Models for Satellite Imagers Using the Optical Design Parameters of a Generic Sensor as Independent Variables

Several types of analytic models are currently used to estimate the spatial response of satellite imagers, the accuracy of these models being critical for applications requiring precise knowledge about the spatial response of a given imager. The assessment of these models is complicated because the actual spatial response of an imager depends on its optical design, so evaluations based on a single kind of design are inherently biased. To reduce this bias, a new assessment methodology based on a generic imaging sensor is proposed; the key optical design’s parameters of this sensor are selected as independent variables, so the error of any spatial response model can be computed within a broad domain of possible optical designs. Assuming a generic sensor with annular optical aperture and square detector elements, the optical factor <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> and the aperture obstruction ratio ε are selected as key design parameters, allowing the error of spatial response models to be computed in the ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> , ε) plane. This approach is used to assess the separable Point Spread Function ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PSF</i> ) model, which assumes that the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PSF</i> is equal to the product of two perpendicular line spread functions, concluding that it is only valid when <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> ≤ 0.35 for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PSF</i> ≥ 0.1. This methodology can be used to assess other types of spatial response models for different shapes of optical apertures and detect or elements. We contend that our approach provides a standard assessment procedure that will help end users select the correct model for their specific application.

Morphology and morphometric diversity of pollen grains of 26 Indian species of &lt;i&gt;Dioscorea&lt;/i&gt; L. (Dioscoreaceae)

Pollen morphology of 26 species of Dioscorea collected from different regions of India was examined critically under LM and SEM to explore their unique features. Pollen grains were monad, isopolar, small to medium-sized (11.3–31 µm). Peroblate, oblate, suboblate and oblate spheroidal (P/E=0.41–0.90) pollen shape, mono and bi-sulcate aperture type and psilate, reticulate, rugulose, strito-reticulate, reticulate-rugulose, punctate and striate exine ornamentation were believed to be some of the important characters for differentiation of closely related species in this studied genus. The comprehensive qualitative and quantitative characters of the pollen grains served as reliable features in taxonomical studies. The observed data were analyzed using PCA and hierarchical clustering to obtain a steady relationship and grouping of the observed species. Histograms, pie chart and bar graph were performed to enumerate the distribution of the quantitative data of various attributes (long axis, short equatorial axis, pollen shape and aperture length). Correlation scatter plot along with density graph helped to understand the interrelationship amongst the studied taxa.

Simulation and Optimization of CNTs Cold Cathode Emission Grid Structure

Carbon nanotubes (CNTs) show significant advantages in the development of cold cathode X-ray tubes due to their excellent field emission performance; however, there are still some problems, such as short lifetime and the low emission current of large-area CNTs. In this paper, a front-grid carbon nanotube array model was established, and the electric field intensity near the tip of the CNTs' electric field enhancement factor was analytically calculated. A simulation model of a CNT three-dimensional field emission electron gun was established by using computer simulation technology (CST). The effects of grid wire diameter, grid aperture shape, and the distribution of grid projection on the cathode surface on the cathode current, anode current, and electron transmission efficiency were analyzed. The aperture ratio was used to evaluate the grid performance, and the simulation results show that the ideal aperture ratio should be between 65% and 85%. A grid structure combining a coarse grid and a fine grid was designed, which can make the electric field intensity around the grid evenly distributed, and effectively increased the cathode emission current by 24.2% compared with the structure without the fine grid. The effect of grid aperture ratio on the electron transmission efficiency was tested. The simulation results and optimized structure can provide a reference for the grid design of cold cathode emission X-ray tubes.

Investigation of the Effects of Anode Geometry on the Electrochemical Degradation of Ni-Ethylenediaminetetraacetic Acid Complexes Using Computational Fluid Dynamics Simulation

Anodic oxidation is a viable technology for the degradation of contaminants such as Ni-ethylenediaminetetraacetic acid (Ni-EDTA) complexes which are commonly found in wastewaters from the electroless plating industry. In an anodic oxidation process, the convective transport of the contaminant to the anode, which is affected by the hydrodynamic characteristics of the reactor and geometry of the electrodes, is crucial to the overall contaminant removal efficiency. In this work, a three-dimensional computational fluid dynamics (CFD) model was successfully developed to investigate flow behavior and its impact on the concentration profiles of Ni-EDTA complexes in a flow-through reactor during anodic oxidation of a synthetic wastewater containing these complexes. The CFD model was used to investigate the effect of electrode aperture size and shape on Ni-EDTA degradation with both simulation and experimental results indicating that, for the investigated system, the reduction of electrode aperture size enhanced the Ni-EDTA degradation rate by up to 1.4 times due to the increased rate of Ni-EDTA mass transfer to the electrode surface. A woven electrode exhibited the highest rate of Ni-EDTA degradation of the different anodes examined with the good performance in this case attributed particularly to the much more uniform Ni-EDTA concentration distribution and surface shear stress on the electrode surface. The CFD model developed in this study provided insights into the effect of electrode aperture geometry on mass transfer and subsequent contaminant removal efficiency and can be used more broadly for the optimization of anode design and reactor operation in electrochemical advanced oxidation processes.

Evaluation of measures related to dosimetric uncertainty of VMAT plans.

Dosimetric uncertainty is most often not included in the process of creating and selecting plans for treatment. Treatment planning and the physician's choice of treatment plan is instead often based only on evaluation of clinical goals of the calculated absorbed dose distribution. Estimation of the dosimetric uncertainty could potentially have impact in the process of comparing and selecting volumetric modulated arc therapy (VMAT) plans. In this study, different measures for estimation of dosimetric uncertainty based on treatment plan parameters for plans with similar dose distributions were evaluated. VMAT plans with similar dose distributions but with different treatment plan designs were created using three different optimization methods for each of ten patient cases (tonsil and prostate cancer). Two plans were optimized in Eclipse, one with and one without the use of aperture shape controller, and one plan was optimized in RayStation. The studied measures related to dosimetric uncertainty of treatment plans were aperture-based complexity metric analysis, investigation of modulation level of multi leaf collimator leaves, gantry speed and dose rate, quasi-3D measurements and evaluation of simulations of realistic delivery variations. The results showed that there can be variations in dosimetric uncertainty for treatment plans with similar dose distributions. Dosimetric uncertainty assessment could therefore have impact on the choice of plan to be used for treatment and lead to a decrease in the uncertainty level of the delivered absorbed dose distribution. This study showed that aperture shape complexity had a larger impact on dosimetric uncertainty compared to modulation level of MLC, gantry speed and dose rate.

The Influence of the Aperture Stop Fractal Shape of an Optical System on the Illuminance Distribution

In the article the options for the application of aperture shapes with fractal properties in the design of optical systems are considered. Calculations of mathematical models of point spread functions of a diffraction-limited optical system are performed. The diffraction patterns of the light distribution in these systems are presented, and the point spread functions are considered for various shapes of the aperture stop. Analytical expressions are obtained for the light distribution depending on the pupil shape, which can be used to control the process of image formation. The pupil shape, which has the shape of an equilateral triangle, is chosen as the basic one, and the shape of the pupil as a "Koch snowflake" curve is also considered. Using the Fraunhofer integral, the dependences of the distribution of the spectral density of the complex amplitude on the aperture located on an opaque screen are derived in the Fraunhofer approximation and under the condition of illumination by a plane monochromatic wave. Using the relationship with the complex amplitude, the sought-for intensity distribution in the plane of the diffraction pattern is obtained. Taking into account the simplifications adopted in this article, the solution of the Fraunhofer integral is found, by setting the integration limits, depending on: the selected aperture profile, the coordinate system chosen for it, and the position of nodal points in this system

A discrete differential evolution with local search particle swarm optimization to direct angle and aperture optimization in IMRT treatment planning problem

Intensity-modulated radiation therapy is a well-known technique for treating cancer patients worldwide. A treatment plan in this technique requires decision-making for three main problems: selection of beam angles, intensity map calculation, and leaf sequencing. Previous works investigated these problems sequentially. We present a new integrated framework for simultaneous decision-making of directions, intensities, and aperture shape, called direct angle and aperture optimization, and develop a mixed-integer nonlinear mathematical model for the problem. Due to the nonlinearity and the dimension of the problem, three efficient metaheuristics based on differential evolution (DE) called classic differential evolution (cDE), discrete differential evolution (dDE), and adaptive hybrid discrete differential evolution-particle swarm optimization (ahdDE-PSO) algorithms are designed to solve the problem. Parameters calibration is performed using the Taguchi design of experiments. The performance of the algorithms is evaluated by solving the problem for ten real cases of liver cancer disease from the TROTS data set. The performed ablation study and statistical analysis of computational results demonstrate that ahdDE-PSO is capable of finding high-quality treatment plans.

Addressing parastomal herniation through biomechanical simulation.

Parastomal hernia remains a significant source of post-operative morbidity. Existing surgical solutions have shown limited success while not addressing the biomechanics underpinning parastomal herniation. The primary objective was to examine the influence of stoma aperture shape on abdominal wall stress and tissue destruction. The secondary objective compared mesh designs with respect to abdominal wall stress. Finite element analysis of an abdominal wall model was used to simulate various stoma and mesh designs. The outcome measures were abdominal wall (mmHg) pressure required to initiate tissue tearing, stress distribution and median and peak abdominal wall stress (N/m2). The simulation demonstrated that the cruciate stoma incision developed high stress concentration at the apices of the slit incisions. The circular stoma incision distributed stress uniformly. The circular stoma design was more resistant to tissue tearing. The Keyhole mesh design demonstrated the lowest median and peak stress at 17.32 and 28.01N/m2. This was a statically significant reduction in stress compared to the Sugar Baker and no mesh designs (p < 0.001).There were no significant differences between the Keyhole mesh design and loose mesh designs as long as the loose mesh design aperture did not exceed 1.5 times the stoma aperture diameter (p = 0.223). This study has demonstrated that the shape of the fascia incision and mesh design have a significant impact on parastomal hernia formation. Novel designs can be used to optimise the stoma. The circular stoma and loose mesh designs are promising avenues for future research.

Window geometry and its effect on the experience of illuminated spaces – a study of three daylit architectural cases

Looking at the architecture of modern housing in Denmark, it seems to express an understanding that equals more daylight with good daylight. With coated energy glass, the windows have increased in size, making glass into a façade material. This means that windows are no longer just holes in the façade but rather make up the entire façade itself. This changes the spatial relationship between the window design and distribution of daylight within the interior space, though we seldom address this lacking a vocabulary and methods. This paper sets out to investigate and experiment with how we can describe and document this change in daylight conditions and how these influence our visual environment, using photographs to record this. The methodology focusses on observations of daylit spaces in three different housing examples in Copenhagen from the 1800s to today. By observing the three daylit spaces, it becomes clear that differences in the size, shape, and position of window apertures influence the qualities of light in a space significantly. Considering that when it comes to window apertures different designs affect the experience of light in a space significantly, it is important to take this into account when designing with daylight. It is also important from a sustainability point of view to include this awareness in future design approaches.

Control of Orbital Angular Momentum Regimen by Modulated Metasurface Leaky-Wave Antennas

In this paper, we present the design procedure of modulated metasurface leaky-wave antennas (MMLWAs) to generate coaxial superposition of vortex beams with several orbital angular momentum (OAM) states. Based on the Flat Optics (FO) technique and aperture field estimation (AFE) method, an analytical framework is proposed to facilitate the implementation of MMLWAs generating multiple topological charges in the OAM regimen. Furthermore, using the spectral analysis which has been derived from the proposed model, we have shown that the symmetry of aperture shape can affect the purity of the mode. Also the perfectly symmetric circular shape is introduced as an ideal choice for high-purity vortex generation. This single aperture antenna with embedded monopole feed can be an appropriate alternative to more complex vortex beam generators such as spiral phase plates and circular antenna arrays.

Characterization of pixelated silicon detectors for daily quality assurance measurements in proton therapy

The advanced imaging and delivery techniques in proton therapy allow conformal high-dose irradiation of the target volume with high accuracy using pencil beam scanning or beam shaping apertures. These irradiation methods increasingly include small radiation fields with large dose gradients, which require detector systems with high spatial resolution for quality assurance. In addition the measurement of all success parameters for daily quality assurance with only one proton field and one simple detector system would save a lot of time in clinical usage. Based on their good spatial resolution and high rate compatibility, pixelated silicon detectors could meet the new requirements. To assess their applicability in proton therapy, ATLAS pixelated silicon detectors are used to measure the lateral beam profile with high spatial resolution. Furthermore, a dose dependent detector calibration is presented to allow the measurement of the requested output constancy. A strategy to verify the proton energy during the daily quality assurance is under study. Promising results from proof-of-principle measurements at the West German Proton Therapy Centre in Essen, Germany, have been obtained.

Channel Aperture Characteristics of Carbonate Apatite Honeycomb Scaffolds Affect Ingrowths of Bone and Fibrous Tissues in Vertical Bone Augmentation.

Synthetic scaffolds with the ability to prevent fibrous tissue penetration and promote bone augmentation may realize guided bone regeneration without the use of a barrier membrane for dental implantation. Here, we fabricated two types of honeycomb scaffolds of carbonate apatite, a bone mineral analog, whose channel apertures were square (HC-S) and rectangular (HC-R). The side lengths of the HC-Ss and HC-Rs were 265.8 ± 8.9; 817.7 ± 2.4 and 267.1 ± 5.2 μm, respectively. We placed cylindrical HC-Ss and HC-Rs on the rabbit calvaria. At 4 weeks post-implantation, the HC-Ss prevented fibrous tissue penetration from the top face via the channels, which allowed the new bone to reach the top of the scaffold from the bottom face or the calvarium. In contrast, in the HC-Rs, fibrous tissues filled the channels in the top region. At 12 weeks post-implantation, the HC-Ss were partially replaced with new bone. In the top region of the HC-Rs, although new bone had formed, fibrous tissue remained. According to the findings here and in our previous study, the longer side length rather than the shorter side length of a rectangular scaffold channel aperture is the dominant factor that affects fibrous tissue penetration and new bone augmentation. Furthermore, even though channel aperture areas are similar, bone and fibrous tissue ingrowths are different when the aperture shapes are different.

Transformer Network Assisted VMAT Optimization

<h3>Purpose/Objective(s)</h3> Aperture shape optimization is one of the most time-consuming parts in VMAT planning. Current state-of-the-art algorithms rely on gradient information to reduce the search space. Here we propose to incorporate past plan knowledge into this key part of optimization. Specifically, we train a deep learning model based on the self-attention mechanism from the transformer architecture, to predict the aperture shapes directly from the patient contour volume. <h3>Materials/Methods</h3> We use a network structure similar to the compact convolutional transformer. It applies convolutions to convert 2D or 3D images to a sequence of embeddings which the transformer can work on. The input to the transformer is the 3D volume of the patient structure set where each voxel number stands for the OAR or PTV type. For each gantry angle from 0, 2, ... to 358, we calculated the ray casting 3D volume at the beams eye view (BEV) coordinates with a size of 32 × 32 × 80 and a resolution of 5 mm. The 180 BEV 3D volumes are tokenized by twelve 3D convolutional layers and flattened to 128 dimensional vectors which are later summed with positional embeddings to preserve the positional information between gantry angles. This is then fed to a transformer encoder which consists of a multi head attention layer with 8 heads and a feed forward layer with a latent dimension of 1024. During the training phase, the 180 aperture shapes, prefixed by a fully closed aperture and represented by 2D matrix with a size of 32 × 32 and resolution of 5 mm, are tokenized in similar ways to the BEV volumes except the convolutional layers are 2D. This is then processed by a decoder with a similar structure to the encoder except with a causal attention mask which forces the prediction to only attend to tokens at earlier locations. This and the encoder output are then sent through another decoder which generates the aperture shapes and weights. At inference phase, a fully closed aperture and BEV volumes are sent into the transformer to predict the next aperture, which are then used as the input to the following apertures. We collected 11 lung SBRT plans as our training data. The transformer is trained using root mean squared propagation with a loss function of binary cross entropy. The DVHs are calculated from the predicted aperture and weighting. <h3>Results</h3> A broadly applicable transformer network for VMAT optimization has been established. The transformer efficiently learns from the training data and predicts apertures close to the past plan. The calculated DVH matches well with the plan data. <h3>Conclusion</h3> The transformer predicted apertures can work as a warm start point for any VMAT optimization algorithms to speed up the clinical workflow. To enhance the robustness and generality of the approach, further study with larger training sets and better model parameters optimization will be useful.

Deep Learning-Based Fluorescence Light Discrimination for High Spatial Resolution Radiotherapy Dose Verification

<h3>Purpose/Objective(s)</h3> High spatial resolution quality assurance techniques are crucial to assess complex dose distributions of modern radiotherapy. Radiation-excited fluorescence imaging has great potential for real-time absolute dosimetry with high spatial resolution. However, the imaging data are generally contaminated by noise due to Cherenkov and scattered lights. This project aims to establish a novel deep learning-based model to correct the fluorescence images for accurate dosimetric applications. <h3>Materials/Methods</h3> An acrylic box phantom containing 1 g/L quinine hemisulfate water solution was constructed. 200 MU single-aperture static beams were delivered to the phantom with varying aperture shapes, gantry angle and collimator angle, and emitted fluorescent signals were detected by a digital camera in 2.0 frames per second cine mode. Temporal filtering and down-sampling were applied to obtain fluorescence images with 1 × 1 mm spatial resolution at the isocenter plane. 2D projected dose distributions were obtained by performing forward projection calculation of the 3D dose distributions calculated by a clinical treatment planning system. The acquired noisy fluorescence images and projected dose distributions were set to inputs and labels of the deep learning modeling, respectively. A 22-layer 2D residual convolutional neural network (CNN) was generated, and 200-epoch supervised learning was performed using 73 training data. For evaluation, accuracy of the calculated projected dose distributions was compared with that of a conventional scatter-kernel deconvolution method. <h3>Results</h3> The deep learning model yielded accurate projected 3D dose distributions with high spatial resolution. In contrast to the conventional method based purely on the analysis of florescence imaging signal, our deep learning-based approach was able to mitigate the adverse effects of Cherenkov and other optical noises. Mean squared error of 7 normalized projected dose distributions in test data were improved from 0.053 for uncorrected to 0.029 for CNN-corrected images. Computation time requiring to calculate a projected dose distribution was 0.2 second with a GPU workstation. <h3>Conclusion</h3> The proposed deep learning-based method improves the fluorescence image quality and the accuracy of dose distribution measurements in nearly real time. This technique will also be applied to Cherenkov radiation removal or signal denoising in other fluorescence imaging modalities. This method will provide an accurate absolute dose verification tool with high spatial resolution.