Methods and considerations to determine sphere center from terrestrial laser scanner point cloud data

Rachakonda, Prem K.; Muralikrishnan, Balasubramanian; Cournoyer, Luc; Cheok, Geraldine S.; Lee, Vincent; Shilling, Meghan; Sawyer, Daniel S.

doi:10.1088/1361-6501/aa8011

Cited by 25 publications

(19 citation statements)

References 9 publications

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“…A detailed description of these properties can be found in Section 4.1. Some studies have already investigated isolated parameters of targets [22][23][24], but no comparison of different commercially available targets has been made yet.…”

Section: Influencing Factors On the Precision Of Target Center Estimamentioning

confidence: 99%

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Decreasing the Uncertainty of the Target Center Estimation at Terrestrial Laser Scanning by Choosing the Best Algorithm and by Improving the Target Design

et al. 2019

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During the registration and georeferencing of terrestrial laser scans, it is common to use targets to mark discrete points. To improve the accuracy of the registration, the uncertainties of the target center estimation (TCE) have to be minimized. The present study examines different factors influencing the precision of the TCE. Here, the focus is on the algorithm and the target design. It is determined that, in general, the uncertainties of the TCE are much smaller than those indicated by the manufacturers. By comparing different algorithms for the first time, it was possible to clearly determine that an algorithm using image correlations yields the smallest standard deviations for the TCE. A comparison of different target designs could not identify an ideal commercially available target. For this reason, a new target, the BOTA8 (BOnn TArget with 8-fold pattern) was developed, which leads to smaller standard deviations than the previous targets. By choosing the best algorithm and improving the target design, standard deviations of 0.5 mm in distance direction and 1.2 arcsec in angular direction for a scan distance up to 100 m were achieved with the laser scanner Leica ScanStation P20. The uncertainties could be reduced by several millimetres and angular seconds compared to the manufacturer’s targets and software.

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Section: Influencing Factors On the Precision Of Target Center Estimamentioning

confidence: 99%

“…When using spherical targets, systematic errors can occur due to one-side scanning of the target [23,25]. These systematic errors are referred to as "squishing" and "flaring" effects.…”

Section: Influencing Factors On the Precision Of Target Center Estimamentioning

confidence: 99%

Decreasing the Uncertainty of the Target Center Estimation at Terrestrial Laser Scanning by Choosing the Best Algorithm and by Improving the Target Design

et al. 2019

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“…The considerations and the process involved in developing the sphere segmentation and fitting algorithm have been detailed by Rachakonda et al [2], and this process to determine a sphere center has been adopted by the ASTM E3125-17 standard. The algorithm works on data corresponding to a single sphere.…”

Section: Description Of the Algorithmmentioning

confidence: 99%

“…Additional data that are not a part of the sphere are allowed, if they are behind the sphere surface. An initial sphere center is calculated using the "closest point algorithm" [2]. Subsequently, a "conecylinder algorithm" [2] is used to find the sphere center, and this process is iterated 5 or more times to calculate the final center of the sphere.…”

Section: Description Of the Algorithmmentioning

confidence: 99%

Software to Determine Sphere Center from Terrestrial Laser Scanner Data per ASTM Standard E3125-17

Rachakonda

Muralikrishnan

Cournoyer

et al. 2018

J. RES. NATL. INST. STAN.

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“…Coordinate metrology is a comprehensive method for measuring the amount of prosthesis misfit. This method involves measuring the actual shape of a workpiece, comparing it with the desired shape, and evaluating metrological information such as size, form, location, and orientation . Probing certain points on the surface with the touch probe and processing the gathered data to formulate the substitute geometry of the workpiece is first performed.…”

mentioning

confidence: 99%

Internal Adaptation of Implant‐Supported, Polymer‐Infused Ceramic Crowns Fabricated by Two CAD/CAM Systems

Talic

Alfadda

2018

Journal of Prosthodontics

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Purpose: The aim of this in vitro study was to compare the internal 3D adaptation of polymer-infused ceramic crowns fabricated using two CAD/CAM systems: CEREC inLab MC XL and Ceramill Motion 2 (5X). Materials and Methods: Twenty-five implant-supported metal-ceramic crowns were fabricated conventionally using the lost-wax technique, and the outer contour was scanned to serve as a guide for designing the polymer-infused ceramic CAD/CAM crowns. Twenty-five crowns were fabricated using CEREC, and 25 crowns were fabricated using Ceramill. The cement space was set to 20 μm. The Zeiss Accura Microsystem Coordinate Measuring Machine (CMM), Calypso, and Geomagic software were used to measure the 3D accuracy of fit of all crowns to their respective implant abutments. To test for the statistical significance between groups in terms of 3D total distortion, a one-way ANOVA was conducted. The Kolmogorov-Smirnov test was used to investigate the differences in the x, y, and z coordinates. A p-value of 0.05 or less was considered statistically significant at an alpha level of 0.05. Results: Comparing the 3D misfit of metal-ceramic crowns to those of CAD/CAM crowns fabricated using CEREC revealed no significant difference (88.20 ± 36.59 μm vs. 102.45 ± 36.58 μm, p = 0.161). Similarly, no significant difference in 3D total distortion was identified between metal-ceramic crowns and crowns fabricated using Ceramill (88.20 ± 36.59 μm vs. 78.40 ± 31.03 μm, p = 0.336); however, the 3D total distortion of polymer-infused crowns made by Ceramill was significantly reduced compared to that of crowns fabricated by CEREC (78.3 ± 31.0 μm vs. 102.4 ± 36.5 μm, p = 0.019). Conclusions: Polymer-infused ceramic crowns fabricated using CEREC exhibited the least accurate 3D fit. All misfit values of the tested groups were within clinically acceptable levels.

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Methods and considerations to determine sphere center from terrestrial laser scanner point cloud data

Cited by 25 publications

References 9 publications

Decreasing the Uncertainty of the Target Center Estimation at Terrestrial Laser Scanning by Choosing the Best Algorithm and by Improving the Target Design

Decreasing the Uncertainty of the Target Center Estimation at Terrestrial Laser Scanning by Choosing the Best Algorithm and by Improving the Target Design

Software to Determine Sphere Center from Terrestrial Laser Scanner Data per ASTM Standard E3125-17

Internal Adaptation of Implant‐Supported, Polymer‐Infused Ceramic Crowns Fabricated by Two CAD/CAM Systems

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