scholarly journals Accuracy of Low-Cost Alternative Facial Scanners: A Prospective Cohort Study.

2021 ◽  
Author(s):  
Alexander K. Bartella ◽  
Josefine Laser ◽  
Mohammad Kamal ◽  
Dirk Halama ◽  
Michael Neuhaus ◽  
...  
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Neck Surgery ◽  
Clinical Analysis ◽  
Smart Device ◽  
Data Sets ◽  
Average Deviation ◽  
Technical Improvement ◽  
Data Set ◽  
Significant Difference

Abstract Introduction: Three-dimensional facial scan images have been showing an increasingly important role in peri-therapeutic management of oral and maxillofacial and head and neck surgery cases. Face scan images can be open using optical facial scanners utilizing line-laser, stereophotography, structured light modality, or from volumetric data obtained from cone beam computed tomography (CBCT). The aim of this study is to evaluate, if two low-cost procedures for creating a three-dimensional face scan images are able to produce a sufficient data set for clinical analysis. Materials and methods: 50 healthy volunteers were included in the study. Two test objects with defined dimensions were attached to the forehead and the left cheek. Anthropometric values were first measured manually, and consecutively, face scans were performed with a smart device and manual photogrammetry and compared to the manually measured data sets.Results: Anthropometric distances on average deviated 2.17 mm from the manual measurement (smart device scanning 3.01 mm vs. photogrammetry 1.34 mm), with 7 out of 8 deviations were statistically significant. Of a total of 32 angles, 19 values showed a significant difference to the original 90° angles. The average deviation was 6.5° (smart device scanning 10.1° vs. photogrammetry 2.8°).Conclusion: Manual photogrammetry with a regular photo-camera shows higher accuracy than scanning with smart device. However, the smart device was more intuitive in handling and further technical improvement of the cameras used should be watched carefully.

Detection of Ureteral Stones in Kidney Ureter Bladder Radiography: Usefulness of Digital Post-processing

2021 ◽  
Vol 17 ◽  
Author(s):  
Sang Lim Choi ◽  
Sung Bin Park ◽  
Seungwook Yang ◽  
Eun Sun Lee ◽  
Hyun Jeong Park ◽  
...  
Keyword(s):  
Detection Sensitivity ◽  
Ureteral Stones ◽  
Data Sets ◽  
Post Processing ◽  
Stone Size ◽  
Data Set ◽  
Detection Rates ◽  
Exact Test ◽  
Significant Difference ◽  
Exact Size

Purpose: Kidney, ureter, and bladder radiography (KUB) has frequently been used in suspected urolithiasis, but its performance is known to be lower than that of computed tomography (CT). This study aimed to investigate the diagnostic performance of digitally post-processed kidney ureter bladder radiography (KUB) in the detection of ureteral stones. Materials And Methods: Thirty patients who underwent digital KUB and CT were included in this retrospective study. The original digital KUB underwent post-processing that involved noise estimation, reduction, and whitening to improve the visibility of ureteral stones. Thus, 60 digital original or post-processed KUB images were obtained and ordered randomly for blinded review. After a period, a second review was performed after unblinding stone laterality. The detection rates were evaluated at both initial and second review, using CT as reference standard. The objective (size) and subjective (visibility) parameters of ureteral stones were analyzed. Fisher’s exact test was used to compare the detection sensitivity between the original and post-processed KUB data set. Visibility analysis was assessed with a paired t-test. Correlation of stone size between CT and digital KUB data sets was assessed with Pearson’s correlation test. Results: The detection rate was higher for most reviewers once stone laterality was provided and was non-significantly better for the post-processed KUB images (p > 0.05). There was no significant difference in stone size among CT and digital KUB data sets. In all reviews, visibility grade was higher in the post-processed KUB images, irrespective of whether stone laterality was provided. Conclusion: Digital post-processing of KUB yielded higher visibility of ureteral stones and could improve stone detection, especially when stone laterality was available. Thus, digitally post-processed KUB can be an excellent modality for detecting ureteral stones and measuring their exact size.

Semi-Automated Roller Parameters Extraction from Terrestrial Lidar

2021 ◽  
Vol 87 (12) ◽  
pp. 879-890
Author(s):  
Sagar S. Deshpande ◽  
Mike Falk ◽  
Nathan Plooster
Keyword(s):  
Rotation Axis ◽  
Moving Average ◽  
Three Dimensional ◽  
Data Sets ◽  
Steel Mill ◽  
Data Set ◽  
Terrestrial Lidar ◽  
Two Dimensional Image ◽  
Average Rotation

Rollers are an integral part of a hot-rolling steel mill. They transport hot metal from one end of the mill to another. The quality of the steel highly depends on the surface quality of the rollers. This paper presents semi-automated methodologies to extract roller parameters from terrestrial lidar points. The procedure was divided into two steps. First, the three-dimensional points were converted to a two-dimensional image to detect the extents of the rollers using fast Fourier transform image matching. Lidar points for every roller were iteratively fitted to a circle. The radius and center of the fitted circle were considered as the average radius and average rotation axis of the roller, respectively. These parameters were also extracted manually and were compared to the measured parameters for accuracy analysis. The proposed methodology was able to extract roller parameters at millimeter level. Erroneously identified rollers were identified by moving average filters. In the second step, roller parameters were determined using the filtered roller points. Two data sets were used to validate the proposed methodologies. In the first data set, 366 out of 372 rollers (97.3%) were identified and modeled. The second, smaller data set consisted of 18 rollers which were identified and modelled accurately.

Geostatistical Joint Interpretation of Gravity and Magnetotelluric Data of the US Cordillera

2021 ◽  
Author(s):  
Mohammad Shehata ◽  
Hideki Mizunaga
Keyword(s):  
Gravity Data ◽  
Three Dimensional ◽  
Data Sets ◽  
Spatial Expansion ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Entire Area ◽  
Mean Values ◽  
Local Means ◽  
The Us

<p>Long-period magnetotelluric and gravity data were acquired to investigate the US cordillera's crustal structure. The magnetotelluric data are being acquired across the continental USA on a quasi-regular grid of ∼70 km spacing as an electromagnetic component of the National Science Foundation EarthScope/USArray Program. International Gravimetreique Bureau compiled gravity Data at high spatial resolution. Due to the difference in data coverage density, the geostatistical joint integration was utilized to map the subsurface structures with adequate resolution. First, a three-dimensional inversion of each data set was applied separately.</p><p>The inversion results of both data sets show a similarity of structure for data structuralizing. The individual result of both data sets is resampled at the same locations using the kriging method by considering each inversion model to estimate the coefficient. Then, the Layer Density Correction (LDC) process's enhanced density distribution was applied to MT data's spatial expansion process. Simple Kriging with varying Local Means (SKLM) was applied to the residual analysis and integration. For this purpose, the varying local means of the resistivity were estimated using the corrected gravity data by the Non-Linear Indicator Transform (NLIT), taking into account the spatial correlation. After that, the spatial expansion analysis of MT data obtained sparsely was attempted using the estimated local mean values and SKLM method at the sections where the MT survey was carried out and for the entire area where density distributions exist. This research presents the integration results and the stand-alone inversion results of three-dimensional gravity and magnetotelluric data.</p>

scholarly journals Three-dimensional evaluation of facial asymmetry in association with unilateral functional crossbite in the primary, early, and late mixed dentition phases

2012 ◽  
Vol 83 (2) ◽  
pp. 253-258 ◽  
Author(s):  
Jasmina Primozic ◽  
Giuseppe Perinetti ◽  
Stephen Richmond ◽  
Maja Ovsenik
Keyword(s):  
Multivariate Analysis ◽  
Three Dimensional ◽  
Facial Asymmetry ◽  
Middle Part ◽  
T Test ◽  
Analysis Of Covariance ◽  
Mixed Dentition ◽  
Data Sets ◽  
Significant Difference ◽  
The Face

ABSTRACT Objective: To assess the degree of facial asymmetry associated with subjects with unilateral functional crossbite (CB) in the primary, early/intermediate, and late mixed dentition phases in comparison with a group of subjects without CB. Subjects and Methods: A group of 234 white subjects, 78 with CB (42 girls and 36 boys) and 156 without CB (73 girls and 83 boys), aged 3.9–11.9, grouped according to the dentition phase, were included. Three-dimensional laser scans of the subjects' faces were used to assess facial asymmetry. For each part of the face two-way multivariate analysis of covariance was performed to assess differences among the subjects, and an independent sample t-test was used to assess the significance of the differences between data sets. Results: Within all dentition phases, the subjects with CB had statistically significantly greater facial asymmetry of the whole face than the subjects without CB, with the greatest values in the lower part of the face (P < .05). In the middle part of the face a significant difference was observed in the mixed dentition phases. Conclusions: Children with unilateral functional CB exhibited a greater facial asymmetry than children without this malocclusion in all the dentition phases herein investigated. The greatest differences were seen for the lower part of the face. Further, facial asymmetry in the middle part of the face became clinically relevant in combination with the transition from primary to mixed dentition phase.

scholarly journals Four-Dimensional Map Reconstruction for Urban Progress Analysis

2020 ◽  
Vol 55 (2) ◽  
Author(s):  
Zahraa E. Hussein ◽  
Marwa M. Bori ◽  
Layla K. Abbas
Keyword(s):  
Spatial Information ◽  
Low Cost ◽  
Three Dimensional ◽  
Water Area ◽  
Google Earth ◽  
Geographical Information ◽  
Data Set ◽  
Important Indicator ◽  
3 Dimensional ◽  
The University

The article describes a simple and low cost methodology of four-dimensional map creation, based on the main elements of the urban world like such as green ground, buildings, soil, water area and others, which makes it possible to detect the urban progress during a certain period using an open source data of Google Earth and geographical information system. This implies that a study of changes in urban elementrequire an integration of spatial information and corresponding real time, which is referred to as the four-dimensional map. Accordingly, the fourth dimensional (time) was added to the three dimensional spatial information (3 dimensional) study area signifies by the University of Baghdad, Aljadrya Campus. Regarding the article, the study area’s urban progress was considered for Google Earth’s available period of the data set that started from 2002 to 2019 at each of 2002, 2005, 2010 in addition to 2019 before being updated from the field observation. The main goal of this article is to provide an important indicator that can be used to determine the nature of current growth and forecast it in the future. Furthermore, it can be used for solving the problems of negative urban progress, which is what most developing countries are experiencing. Findings show significant changes in the main objects of the study area are represented by increasing each of buildings, green grounds, play grounds by about 40.9%, 65.4% and 30.2% respectively, which are offset by decrease insoil grounds of nearly 20.8%.

scholarly journals EcoDes-DK15: High-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set

2021 ◽  
Author(s):  
Jakob J. Assmann ◽  
Jesper E. Moeslund ◽  
Urs A. Treier ◽  
Signe Normand
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Airborne Laser Scanning ◽  
Data Sets ◽  
Ecosystem Structure ◽  
Data Set ◽  
Vegetation Height ◽  
Airborne Laser

Abstract. Biodiversity studies could strongly benefit from three-dimensional data on ecosystem structure derived from contemporary remote sensing technologies, such as Light Detection and Ranging (LiDAR). Despite the increasing availability of such data at regional and national scales, the average ecologist has been limited in accessing them due to high requirements on computing power and remote-sensing knowledge. We processed Denmark's publicly available national Airborne Laser Scanning (ALS) data set acquired in 2014/15 together with the accompanying elevation model to compute 70 rasterized descriptors of interest for ecological studies. With a grain size of 10 m, these data products provide a snapshot of high-resolution measures including vegetation height, structure and density, as well as topographic descriptors including elevation, aspect, slope and wetness across more than forty thousand square kilometres covering almost all of Denmark's terrestrial surface. The resulting data set is comparatively small (~ 87 GB, compressed 16.4 GB) and the raster data can be readily integrated into analytical workflows in software familiar to many ecologists (GIS software, R, Python). Source code and documentation for the processing workflow are openly available via a code repository, allowing for transfer to other ALS data sets, as well as modification or re-calculation of future instances of Denmark’s national ALS data set. We hope that our high-resolution ecological vegetation and terrain descriptors (EcoDes-DK15) will serve as an inspiration for the publication of further such data sets covering other countries and regions and that our rasterized data set will provide a baseline of the ecosystem structure for current and future studies of biodiversity, within Denmark and beyond.

scholarly journals A RELIABILITY EVALUATION SYSTEM OF ASSOCIATION RULES

2016 ◽  
Vol III-2 ◽  
pp. 53-60
Author(s):  
Jiangping Chen ◽  
Wanshu Feng ◽  
Minghai Luo
Keyword(s):  
Association Rules ◽  
Evaluation System ◽  
Three Dimensional ◽  
Reliability Evaluation ◽  
Data Sets ◽  
Simulation Data ◽  
Data Set ◽  
Actual Problem ◽  
Research Fields ◽  
Rule Evaluation

In mining association rules, the evaluation of the rules is a highly important work because it directly affects the usability and applicability of the output results of mining. In this paper, the concept of reliability was imported into the association rule evaluation. The reliability of association rules was defined as the accordance degree that reflects the rules of the mining data set. Such degree contains three levels of measurement, namely, accuracy, completeness, and consistency of rules. To show its effectiveness, the "accuracy-completeness-consistency" reliability evaluation system was applied to two extremely different data sets, namely, a basket simulation data set and a multi-source lightning data fusion. Results show that the reliability evaluation system works well in both simulation data set and the actual problem. The three-dimensional reliability evaluation can effectively detect the useless rules to be screened out and add the missing rules thereby improving the reliability of mining results. Furthermore, the proposed reliability evaluation system is applicable to many research fields; using the system in the analysis can facilitate obtainment of more accurate, complete, and consistent association rules.

scholarly journals Zonal-mean data set of global atmospheric reanalyses on pressure levels

2018 ◽  
Author(s):  
Patrick Martineau ◽  
Jonathon S. Wright ◽  
Nuanliang Zhu ◽  
Masatomo Fujiwara
Keyword(s):  
Three Dimensional ◽  
Short Wave ◽  
Reanalysis Data ◽  
Environmental Data ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Intercomparison Project ◽  
Complete Set ◽  
Transformed Eulerian Mean

Abstract. This data set, which is prepared for the SPARC-Reanalysis Intercomparison Project (S-RIP), provides several zonal-mean diagnostics computed from reanalysis data on pressure levels. Diagnostics are currently provided for a variety of reanalyses, including ERA-40, ERA-Interim, ERA-20C, NCEP-NCAR, NCEP-DOE, CFSR, 20CR v2 and v2c, JRA-25, JRA-55, JRA-55C, JRA-55AMIP, MERRA, and MERRA-2. The data set will be expanded to include additional reanalyses as they become available. Basic dynamical variables (such as temperature, geopotential height and three-dimensional winds) are provided in addition to a complete set of terms from the Eulerian-mean and transformed Eulerian-mean momentum equations. Total diabatic heating and its long-wave and short-wave components are included as availability permits, along with heating rates diagnosed from the basic dynamical variables using the zonal-mean thermodynamic equation. Two versions of the data set are provided, one that uses horizontal and vertical grids provided by the various reanalysis centers, and another that uses a common grid to facilitate comparison among data sets. For the common grid, all diagnostics are interpolated horizontally onto a regular 2.5° ×2.5° grid for a subset of pressure levels that are common amongst all included reanalyses. The dynamical (Martineau, 2017, http://dx.doi.org/10.5285/b241a7f536a244749662360bd7839312) and diabatic (Wright, 2017, http://dx.doi.org/10.5285/70146c789eda4296a3c3ab6706931d56) variables are archived and maintained by the Centre for Environmental Data Analysis (CEDA).

scholarly journals Atmospheric observations made at Oliktok Point, Alaska as part of the Profiling at Oliktok Point to Enhance YOPP Experiments (POPEYE) campaign

2019 ◽  
Author(s):  
Gijs de Boer ◽  
Darielle Dexheimer ◽  
Fan Mei ◽  
John Hubbe ◽  
Casey Longbottom ◽  
...  
Keyword(s):  
Layer Structure ◽  
Three Dimensional ◽  
Unmanned Aircraft ◽  
Department Of Energy ◽  
Atmospheric Radiation ◽  
Data Sets ◽  
Radiation Measurement ◽  
Data Set ◽  
Atmospheric Radiation Measurement ◽  
Aerosol Properties

Abstract. Between 1 July and 30 September 2018, small unmanned aircraft systems (sUAS), tethered balloon systems (TBS), and additional radiosondes were deployed at Oliktok Point, Alaska to measure the atmosphere in support of the second special observing period for the Year of Polar Prediction (YOPP). These measurements, collected as part of the “Profiling at Oliktok Point to Enhance YOPP Experiments” (POPEYE) campaign, targeted quantities related to enhancing our understanding of boundary layer structure, cloud and aerosol properties and surface-atmosphere exchange, and provide extra information for model evaluation and improvement work. Over the three-month campaign, a total of 59 DataHawk2 sUAS flights, 52 TBS flights, and 238 total radiosonde launches were completed as part of POPEYE. The data from these coordinated activities provide a comprehensive three-dimensional data set of the atmospheric state (air temperature, humidity, pressure, and wind), surface skin temperature, aerosol properties, and cloud microphysical information over Oliktok Point. These data sets have been checked for quality and submitted to the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program data archive (http://www.archive.arm.gov/discovery/) and are accessible at no cost by all registered users. The primary dataset DOIs are https://doi.org/10.5439/1418259 (DataHawk2 measurements; Atmospheric Radiation Measurement Program, 2016b), https://doi.org/10.5439/1426242 (TBS measurements; Atmospheric Radiation Measurement Program, 2017) and https://doi.org/10.5439/1021460 (radiosonde measurements; Atmospheric Radiation Measurement Program, 2013a).

scholarly journals Measuring change at Earth’s surface: On-demand vertical and three- dimensional topographic differencing implemented in OpenTopography

Geosphere ◽  
2021 ◽  
Author(s):  
Chelsea Scott ◽  
Minh Phan ◽  
Viswanath Nandigam ◽  
Christopher Crosby ◽  
J Ramon Arrowsmith
Keyword(s):  
Three Dimensional ◽  
Point Clouds ◽  
Data Sets ◽  
Data Set ◽  
Landscape Characteristics ◽  
On Demand ◽  
Digital Elevation ◽  
Rigid Deformation ◽  
Optimal Resolution ◽  
Topography Data

Topographic differencing measures landscape change by comparing multitemporal high-resolution topography data sets. Here, we focused on two types of topographic differencing: (1) Vertical differencing is the subtraction of digital elevation models (DEMs) that span an event of interest. (2) Three-dimensional (3-D) differencing measures surface change by registering point clouds with a rigid deformation. We recently released topo­graphic differencing in OpenTopography where users perform on-demand vertical and 3-D differencing via an online interface. OpenTopography is a U.S. National Science Foundation–funded facility that provides access to topographic data and processing tools. While topographic differencing has been applied in numerous research studies, the lack of standardization, particularly of 3-D differencing, requires the customization of processing for individ­ual data sets and hinders the community’s ability to efficiently perform differencing on the growing archive of topography data. Our paper focuses on streamlined techniques with which to efficiently difference data sets with varying spatial resolution and sensor type (i.e., optical vs. light detection and ranging [lidar]) and over variable landscapes. To optimize on-demand differencing, we considered algorithm choice and displacement resolution. The optimal resolution is controlled by point density, landscape characteristics (e.g., leaf-on vs. leaf-off), and data set quality. We provide processing options derived from metadata that allow users to produce optimal high-quality results, while experienced users can fine tune the parameters to suit their needs. We anticipate that the differencing tool will expand access to this state-of-the-art technology, will be a valuable educational tool, and will serve as a template for differencing the growing number of multitemporal topography data sets.

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