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Low-cost optical sensor to automatically monitor and control biomass concentration in microalgal cultivation
Not Available
Automatic identification of wind turbine models using evolutionary multiobjective optimization
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Communication: Automatic code generation enables nuclear gradient computations for fully internally contracted multireference theory
Analytical nuclear gradients for fully internally contracted complete active space second-order perturbation theory (CASPT2) are reported. This implementation has been realized by an automated code generator that can handle spin-free formulas for the CASPT2 energy and its derivatives with respect to variations of molecular orbitals and reference coefficients. The underlying complete active space self-consistent field and the so-called Z-vector equations are solved using density fitting. The implementation has been applied to the vertical and adiabatic ionization potentials of the porphin molecule to illustrate its capability.
Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or an investigation for maximizing their effectiveness. We carry out a comparison between several common machine learning methods for galaxy classification [Convolutional Neural Network (CNN), K-nearest neighbour, logistic regression, Support Vector Machine, Random Forest, and Neural Networks] by using Dark Energy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project (GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of ~2800 galaxies with visual classification from GZ1, we reach an accuracy of ~0.99 for the morphological classification of ellipticals and spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both ellipticals and spirals. We confirm that ~2.5 percent galaxies are misclassified by GZ1 in our study. After correcting these galaxies’ labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result).
Empirical Investigations of the Opportunity Limits of Automatic Residential Electric Load Shaping
Residential electric load shaping is often modeled as infrequent, utility-initiated, short-duration deferral of peak demand through direct load control. In contrast, modeled herein is the potential for frequent, transactive, intraday, consumer-configurable load shaping for storage-capable thermostatically controlled electric loads (TCLs), including refrigerators, freezers, and hot water heaters. Unique to this study are 28 months of 15-minute-interval observations of usage in 101 homes in the Pacific Northwest United States that specify exact start, duration, and usage patterns of approximately 25 submetered loads per home. The magnitudes of the load shift from voluntarily-participating TCL appliances are aggregated to form hourly upper and lower load-shaping limits for the coordination of electrical generation, transmission, distribution, storage, and demand. Empirical data are statistically analyzed to define metrics that help quantify load-shaping opportunities.
Automatic and Transparent Resource Contention Mitigation for Improving Large-Scale Parallel File System Performance
Proportional to the scale increases in HPC systems, many scientific applications are becoming increasingly data intensive, and parallel I/O has become one of the dominant factors impacting the large-scale HPC application performance. On a typical large-scale HPC system, we have observed that the lack of a global workload coordination coupled with the shared nature of storage systems cause load imbalance and resource contention over the end-to-end I/O paths resulting in severe performance degradation. I/O load imbalance on HPC systems is generally a self-inflicted wound and mostly occurs between the I/O paths and resources consumed by each individual job. In this paper, we introduce TAPP-IO, a dynamic, shared load balancing framework for mitigating resource contention. TAPP-IO extends our previous work and solves two major limitations: First, it transparently intercepts file creation calls during runtime to balance the workload over all available storage targets. The usage of TAPP-IO requires no application source code modifications and is independent from any I/O middleware. The framework can be applied to almost any HPC platform and is suitable for systems that lack a centralized file system resource manager. Second, the framework proposes a new placement strategy to support not only file-per-process I/O, but also single shared file I/O. This opens the door to a new class of scientific applications that can leverage the placement library for improved performance. We demonstrate the effectiveness of our integration on the Titan system at the Oak Ridge National Laboratory. Our experiments with a synthetic benchmark and real-world HPC workload show that, even in a noisy production environment, TAPP-IO can improve large-scale application performance significantly.
Automatic Data Processing and Data Display System for the HERMES III Accelerator.
Abstract not provided.
Parametrization of textural patterns in {sup 123}I-ioflupane imaging for the automatic detection of Parkinsonism
Purpose: A novel approach to a computer aided diagnosis system for the Parkinson's disease is proposed. This tool is intended as a supporting tool for physicians, based on fully automated methods that lead to the classification of{sup 123}I-ioflupane SPECT images. Methods: {sup 123}I-ioflupane images from three different databases are used to train the system. The images are intensity and spatially normalized, then subimages are extracted and a 3D gray-level co-occurrence matrix is computed over these subimages, allowing the characterization of the texture using Haralick texture features. Finally, different discrimination estimation methods are used to select a feature vector that can be used to train and test the classifier. Results: Using the leave-one-out cross-validation technique over these three databases, the system achieves results up to a 97.4% of accuracy, and 99.1% of sensitivity, with positive likelihood ratios over 27. Conclusions: The system presents a robust feature extraction method that helps physicians in the diagnosis task by providing objective, operator-independent textural information about{sup 123}I-ioflupane images, commonly used in the diagnosis of the Parkinson's disease. Textural features computation has been optimized by using a subimage selection algorithm, and the discrimination estimation methods used here makes the system feature-independent, allowing us to extend it to other databases and diseases.
Method for automatic correction of offset drift in online sensors
Abstract Successful operation and optimization of water treatment systems hinge on the availability of high-quality online sensor measurements. Ideally, the available measurements should be simultaneously accurate (i.e., unbiased and precise), representative, voluminous, and timely. This remains a pain-point in current water infrastructures, forming a barrier to a wider adoption of advanced and autonomous control systems. While short-lived symptoms, such as outliers and spikes, can be detected or corrected with state-of-the-art tools for fault detection and identification, it is much more difficult to detect, diagnose, and correct the symptoms of slow faults, such as changes in offset or sensitivity due to drift. The time scale of drift is often longer than the time scales of the system dynamics of interest. Moreover, sensor drift has been shown to occur at the same time and with similar rates when sensors are exposed to the same conditions. This challenges data quality management strategies based on redundancy. In this contribution, we develop a new method, including both a hands-off sensor calibration mechanism and an information-seeking control architecture that can handle the unique challenge of simultaneous and similar drift in online sensors.
Automatic tracking of arbitrarily shaped implanted markers in kilovoltage projection images: A feasibility study
Purpose: Certain types of commonly used fiducial markers take on irregular shapes upon implantation in soft tissue. This poses a challenge for methods that assume a predefined shape of markers when automatically tracking such markers in kilovoltage (kV) radiographs. The authors have developed a method of automatically tracking regularly and irregularly shaped markers using kV projection images and assessed its potential for detecting intrafractional target motion during rotational treatment. Methods: Template-based matching used a normalized cross-correlation with simplex minimization. Templates were created from computed tomography (CT) images for phantom studies and from end-expiration breath-hold planning CT for patient studies. The kV images were processed using a Sobel filter to enhance marker visibility. To correct for changes in intermarker relative positions between simulation and treatment that can introduce errors in automatic matching, marker offsets in three dimensions were manually determined from an approximately orthogonal pair of kV images. Two studies in anthropomorphic phantom were carried out, one using a gold cylindrical marker representing regular shape, another using a Visicoil marker representing irregular shape. Automatic matching of templates to cone beam CT (CBCT) projection images was performed to known marker positions in phantom. In patient data, automatic matching was compared to manual matching as an approximate ground truth. Positional discrepancy between automatic and manual matching of less than 2 mm was assumed as the criterion for successful tracking. Tracking success rates were examined in kV projection images from 22 CBCT scans of four pancreas, six gastroesophageal junction, and one lung cancer patients. Each patient had at least one irregularly shaped radiopaque marker implanted in or near the tumor. In addition, automatic tracking was tested in intrafraction kV images of three lung cancer patients with irregularly shaped markers during 11 volumetric modulated arc treatments. Purpose-built software developed at our institution was used to create marker templates and track the markers embedded in kV images. Results: Phantom studies showed mean ± standard deviation measurement uncertainty of automatic registration to be 0.14 ± 0.07 mm and 0.17 ± 0.08 mm for Visicoil and gold cylindrical markers, respectively. The mean success rate of automatic tracking with CBCT projections (11 frames per second, fps) of pancreas, gastroesophageal junction, and lung cancer patients was 100%, 99.1% (range 98%–100%), and 100%, respectively. With intrafraction images (approx. 0.2 fps) of lung cancer patients, the success rate was 98.2% (range 97%–100%), and 94.3% (range 93%–97%) using templates from 1.25 mm and 2.5 mm slice spacing CT scans, respectively. Correction of intermarker relative position was found to improve the success rate in two out of eight patients analyzed. Conclusions: The proposed method can track arbitrary marker shapes in kV images using templates generated from a breath-hold CT acquired at simulation. The studies indicate its feasibility for tracking tumor motion during rotational treatment. Investigation of the causes of misregistration suggests that its rate of incidence can be reduced with higher frequency of image acquisition, templates made from smaller CT slice spacing, and correction of changes in intermarker relative positions when they occur.
WE-A-17A-06: Evaluation of An Automatic Interstitial Catheter Digitization Algorithm That Reduces Treatment Planning Time and Provide Means for Adaptive Re-Planning in HDR Brachytherapy of Gynecologic Cancers
Purpose: To evaluate an automatic interstitial catheter digitization algorithm that reduces treatment planning time and provide means for adaptive re-planning in HDR Brachytherapy of Gynecologic Cancers. Methods: The semi-automatic catheter digitization tool utilizes a region growing algorithm in conjunction with a spline model of the catheters. The CT images were first pre-processed to enhance the contrast between the catheters and soft tissue. Several seed locations were selected in each catheter for the region growing algorithm. The spline model of the catheters assisted in the region growing by preventing inter-catheter cross-over caused by air or metal artifacts. Source dwell positions from day one CT scans were applied to subsequent CTs and forward calculated using the automatically digitized catheter positions. This method was applied to 10 patients who had received HDR interstitial brachytherapy on an IRB approved image-guided radiation therapy protocol. The prescribed dose was 18.75 or 20 Gy delivered in 5 fractions, twice daily, over 3 consecutive days. Dosimetric comparisons were made between automatic and manual digitization on day two CTs. Results: The region growing algorithm, assisted by the spline model of the catheters, was able to digitize all catheters. The difference between automatic and manually digitized positions was 0.8±0.3 mm. The digitization time ranged from 34 minutes to 43 minutes with a mean digitization time of 37 minutes. The bulk of the time was spent on manual selection of initial seed positions and spline parameter adjustments. There was no significance difference in dosimetric parameters between the automatic and manually digitized plans. D90% to the CTV was 91.5±4.4% for the manual digitization versus 91.4±4.4% for the automatic digitization (p=0.56). Conclusion: A region growing algorithm was developed to semi-automatically digitize interstitial catheters in HDR brachytherapy using the Syed-Neblett template. This automatic digitization tool was shown to be accurate compared to manual digitization.
An automatic input/output test experience of FPGA-based logic controller with I/O stimulator - 282
This paper describes an automatic testing approach instead of a traditional manual test for an FPGA-based Logic Controller (FLC). It mainly describes an automatic testing of FLC using an I/O stimulator with the initiated manual action. The FLC was developed by Doosan Heavy Industry and KAERI in S. Korea. We also developed a test-bed like I/O stimulator for a burning test based on the operational scenario. Signal sources from the I/O stimulator contain an analog input, an analog output, a digital input and a digital output, a programmable power supply, an RS232C serial interface, and a dual port Ethernet interface. LabVIEW Programming was used for the automatic testing. The FLC consists of a general processor module (FPM-01), a complex processor module (FPM-02), analog input modules (FAI-01), analog output modules (FAO-01), digital input modules (FDI-01), digital output modules (FDO-01), a data link module (FDL-01), and a network module (FNW-01). Among these, in this paper, automatic digital I/O testing and automatic analog I/O testing are described. In addition, for the accuracy of the automatic testing, two graphic recorders are used. One is the output results of general processor based testing, and the other is the output results of complex processor based testing. These are different company products. Redundancy recording was found in the test results. The test results were synchronized internally with the existing I/O stimulator and externally with two graphic recorders. Calibrations of all of the equipment were made before the system testing. Before the testing started, a test plan and the test procedure were set up in advance, and we performed test scenario-based automatic functional testing for the FLC as the qualification process. It can be several executed depending on the scenario and conditional parameters of the test. For validation of the accuracy and reliability in our automated test, manual testing was also performed. Manual tests were conducted in two ways. The first one was a manual test using Fluke 754 and Fluke 715. The other one was using embedded manual features of the I/O stimulator. By performing the automatic input and output testing using the I/O stimulator, the time and expense of FLC testing can be reduced significantly compared with a conventional manual test. We rechecked the automatic test results using Fluke754 manually. (authors)
Development and Implementation of an Automatic Continuous Online Monitoring and Control Platform for Polymerization Reactions to Sharply Boost Energy and Resource Efficiency in Polymer Manufacturing
The project goal was to create an energy saving paradigm shift in how polymers are manufactured in the 21st century. It used Automatic Continuous Online Monitoring of Polymerization reactions (ACOMP) integrated for the first time with automatic active control to create the innovative ‘ACOMP/Control Interface’, or ‘ACOMP/CI’. ACOMP/CI will begin the transformation from old, inefficient processes into highly evolved, energy and resource efficient ones. The ACOMP platform is broadly applicable to many types of reactions and processes throughout the vast polymer industry. The industry provides materials for sectors such as automotive, aerospace, oil recovery, agriculture, paints, resins, adhesives, pharmaceuticals and therapeutic proteins, optics, electronics, lightweight building materials, and many more. The U.S. chemical industry is one of the last major sectors in which the U.S. has top global stature. It consumes 24% of all U.S. manufacturing energy, produces over $800B of product annually, supports 25% of the U.S. GDP and employs over 6 million people. It is also a major source of GHG emissions. Polymers make up approximately 30% of this sector. It is estimated that annually 60 TBtu of energy could be saved and 3 million tons less of GHG emissions produced by optimizing production in the polyolefin manufacturing sector alone. The project scope included first time design and prototyping of an ACOMP/CI, creation of active reaction controllers, and demonstration of control capabilities on ideal, low concentration polymerization reactions. All these elements of the scope were met, including advances and findings not originally anticipated. Extensions to more complex reactions, beyond the reactor capabilities of the current project ACOMP/CI, such as polyolefins and other high pressure/high temperature reactions, are being proposed in Fall 2017 to CESMII, a DoE based NNMI. The initial proposal was for a three year funded project, but this was reduced to a two year project and budget due to funding constraints. Hence, some of the original plans, such as adaptation of the ACOMP/CI to more relevant industrial processes, such as emulsion and dispersion technologies, could not be carried out. A third year of funding was requested at the end of the project, but DoE did not have resources to grant this. The sub-contractor Fluence Analytics (previously Advanced Polymer Monitoring Technologies, Inc) designed, prototyped, and commissioned a working ACOMP/CI by June 2015. The reaction characteristics to be automatically controlled were i) conversion kinetics, ii) molecular weight, iii) copolymer composition, and iv) simultaneous molecular weight and composition. A two pronged control strategy was used. The Tulane/Fluence group took a basic principles approach that did not rely on kinetic models. The LSU group took a more complex, non-linear model-oriented approach involving complete kinetic descriptions of the reaction system Each of these approaches proved successful in their own way. By April 2016 fully automatic control of conversion and weight average molecular weight, Mw, trajectories was achieved using the Tulane/Fluence (TF) basic principles controller. Similar results were obtained by the LSU non-linear model controller by August 2016. The demonstration system was aqueous free radical polymerization of acrylamide, Am. The control variables were temperature and semi-batch feed to the reactor of Am monomer and initiator. A demonstration of active manual conversion control in an industrial process using high solids in inverse emulsion polymerization of Am was achieved. During Summer 2016 the TF controller was used in conjunction with a chain transfer agent, another control variable, to automatically produce multi-modal molecular weight distributions, MWD, in a single reactor. Industrially, multi-modal MWD are produced by mixing products made in separate reactors, requiring significant extra time, energy, and reactor resources. Recognizing the industrial potential a patent on automatic production of multi-modal polymers was filed, and DoE acknowledged. In Fall 2016 the TF team developed a basic principles controller for copolymer composition and demonstrated it on aqueous free radical copolymerization of comonomers Am and styrene sulfonate, SS. TF then fused the Mw and composition controllers to achieve simultaneous control of both Mw and copolymer composition trajectories. Numerous simultaneous trajectories were demonstrated, including a trimodal composition distribution with constant Mw. Meanwhile, the LSU group developed a Kalman filter to improve the results of their automatic Mw and conversion controller and successful tests were made. During the project the TF team developed a means of computing full MWD during polymer synthesis without need for any chromatographic separation, based on model distributions. This means the polymer product is ‘born characterized’ and this can eliminate post-manufacture analytical laboratory quality control. TF filed a joint patent application on this new approach to chromatography-free determination of MWD with acknowledgment to DoE. The Tulane group obtained a 60MHz NMR during the project and recently completed the first work on separating three comonomers, Am, SS, and Na-acrylate, with a first demonstration of terpolymer composition control with the TF basic principles controller. Widespread dissemination of ACOMP/CI in the polymer manufacturing sector will bolster DoE goals of energy efficiency and reduced GHG emissions: The ability to monitor and actively control polymerization reactions will lead to more efficient use of energy and non-renewable resources, plant and labor time, increase the safety of manufacturing personnel, and will enhance product quality and lead to feasibility of manufacturing of polymers currently too complex for industrial scale production, while leading to less GHG emissions per kilo of product, and allowing for increased U.S. competitiveness in this enormous manufacturing sector. When ACOMP/CI is expanded to the polyolefin industry it is estimated that 60 TeraBTU/year of energy can be saved. Much of this saving is anticipated to come from optimized control of grade changeovers in steady state reactors and maintenance of steady states. Conclusions: ACOMP’s ability to provide continuous realtime data streams of measured polymer and reaction characteristics made it possible, for the first time, to directly and automatically control free radical polymerization reactions. An industrial client of Fluence Analytics has requisitioned the first ACOMP/CI which uses the TF basic principles controller. This sets the stage for FA to add control features to the ACOMP systems it has begun to install on the industrial scale beginning in 2014. Recommendations: This successful project was mainly limited to ideal polymerizations not of an industrial sort. The most energy intensive portion of polymer manufacturing is polyolefins. Adoption of ACOMP/CI to this enormous industrial sector faces the enormous challenges of high temperature, high pressure continuous sampling and high temperature sensor operation to obtain the continuous data needed for direct reaction control. The project team has a strategy for achieving this ambitious goal and will present it in Fall 2017 as a proposal to CESMII/DoE. It is recommended that this upcoming proposal be funded in order to make full use of the achievements of this just ended DoE project as the next step towards making polyolefin ACOMP/CI an energy saving reality. It is projected that ACOMP/CI can have its first polyolefin testbed demonstrations within two years of beginning the proposed project.
TU-F-17A-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - An Automatic Toolkit for Efficient and Robust Analysis of 4D Respiratory Motion
Purpose: To provide an automatic image analysis toolkit to process thoracic 4-dimensional computed tomography (4DCT) and extract patient-specific motion information to facilitate investigational or clinical use of 4DCT. Methods: We developed an automatic toolkit in MATLAB to overcome the extra workload from the time dimension in 4DCT. This toolkit employs image/signal processing, computer vision, and machine learning methods to visualize, segment, register, and characterize lung 4DCT automatically or interactively. A fully-automated 3D lung segmentation algorithm was designed and 4D lung segmentation was achieved in batch mode. Voxel counting was used to calculate volume variations of the torso, lung and its air component, and local volume changes at the diaphragm and chest wall to characterize breathing pattern. Segmented lung volumes in 12 patients are compared with those from a treatment planning system (TPS). Voxel conversion was introduced from CT# to other physical parameters, such as gravity-induced pressure, to create a secondary 4D image. A demon algorithm was applied in deformable image registration and motion trajectories were extracted automatically. Calculated motion parameters were plotted with various templates. Machine learning algorithms, such as Naive Bayes and random forests, were implemented to study respiratory motion. This toolkit is complementary to and will be integrated with the Computational Environment for Radiotherapy Research (CERR). Results: The automatic 4D image/data processing toolkit provides a platform for analysis of 4D images and datasets. It processes 4D data automatically in batch mode and provides interactive visual verification for manual adjustments. The discrepancy in lung volume calculation between this and the TPS is <±2% and the time saving is by 1–2 orders of magnitude. Conclusion: A framework of 4D toolkit has been developed to analyze thoracic 4DCT automatically or interactively, facilitating both investigational and clinical use. More software tools are under development for automatic analysis of other 4D imaging modalities. This research is in part supported by NIH (U54CA137788/132378) and City Seed FY13(Grant No. 93348-14 01). AY would like to thank MSKCC summer medical student research program supported by National Cancer Institute and hosted by Department of Medical Physics at MSKCC.
Phantom Study Investigating the Accuracy of Manual and Automatic Image Fusion with the GE Logiq E9: Implications for use in Percutaneous Liver Interventions
PurposeTo determine the accuracy of automatic and manual co-registration methods for image fusion of three-dimensional computed tomography (CT) with real-time ultrasonography (US) for image-guided liver interventions.Materials and MethodsCT images of a skills phantom with liver lesions were acquired and co-registered to US using GE Logiq E9 navigation software. Manual co-registration was compared to automatic and semiautomatic co-registration using an active tracker. Also, manual point registration was compared to plane registration with and without an additional translation point. Finally, comparison was made between manual and automatic selection of reference points. In each experiment, accuracy of the co-registration method was determined by measurement of the residual displacement in phantom lesions by two independent observers.ResultsMean displacements for a superficial and deep liver lesion were comparable after manual and semiautomatic co-registration: 2.4 and 2.0 mm versus 2.0 and 2.5 mm, respectively. Both methods were significantly better than automatic co-registration: 5.9 and 5.2 mm residual displacement (p < 0.001; p < 0.01). The accuracy of manual point registration was higher than that of plane registration, the latter being heavily dependent on accurate matching of axial CT and US images by the operator. Automatic reference point selection resulted in significantly lower registration accuracy compared to manual point selection despite lower root-mean-square deviation (RMSD) values.ConclusionThe accuracy of manual and semiautomatic co-registration is better than that of automatic co-registration. For manual co-registration using a plane, choosing the correct plane orientation is an essential first step in the registration process. Automatic reference point selection based on RMSD values is error-prone.
SU-E-T-362: Automatic Catheter Reconstruction of Flap Applicators in HDR Surface Brachytherapy
Purpose: Catheter reconstruction is crucial for the accurate delivery of radiation dose in HDR brachytherapy. The process becomes complicated and time-consuming for large superficial clinical targets with a complex topology. A novel method for the automatic catheter reconstruction of flap applicators is proposed in this study. Methods: We have developed a program package capable of image manipulation, using C++class libraries of The-Visualization-Toolkit(VTK) software system. The workflow for automatic catheter reconstruction is: a)an anchor point is placed in 3D or in the axial view of the first slice at the tip of the first, last and middle points for the curved surface; b)similar points are placed on the last slice of the image set; c)the surface detection algorithm automatically registers the points to the images and applies the surface reconstruction filter; d)then a structured grid surface is generated through the center of the treatment catheters placed at a distance of 5mm from the patient's skin. As a result, a mesh-style plane is generated with the reconstructed catheters placed 10mm apart. To demonstrate automatic catheter reconstruction, we used CT images of patients diagnosed with cutaneous T-cell-lymphoma and imaged with Freiburg-Flap-Applicators (Nucletron™-Elekta, Netherlands). The coordinates for each catheter were generated and compared to the control points selected during the manual reconstruction for 16catheters and 368control point Results: The variation of the catheter tip positions between the automatically and manually reconstructed catheters was 0.17mm(SD=0.23mm). The position difference between the manually selected catheter control points and the corresponding points obtained automatically was 0.17mm in the x-direction (SD=0.23mm), 0.13mm in the y-direction (SD=0.22mm), and 0.14mm in the z-direction (SD=0.24mm). Conclusion: This study shows the feasibility of the automatic catheter reconstruction of flap applicators with a high level of positioning accuracy. Implementation of this technique has potential to decrease the planning time and may improve overall quality in superficial brachytherapy.