The Analysis of the Registration Accuracy of Distributed Drives Parameters

2014 ◽  
pp. 73-80 ◽  
Author(s):  
Mariusz Piotr Hetmańczyk ◽  
Jerzy Świder ◽  
Grzegorz Wszołek
Keyword(s):  
Registration Accuracy

Registration and Fusion of UAV LiDAR System Sequence Images and Laser Point Clouds

2020 ◽  
Author(s):  
Jiayong Yu ◽  
Longchen Ma ◽  
Maoyi Tian, ◽  
Xiushan Lu
Keyword(s):  
Point Cloud ◽  
Image Data ◽  
Point Clouds ◽  
Optical Image ◽  
Point Cloud Data ◽  
Feature Points ◽  
Lidar System ◽  
Registration Accuracy ◽  
Cloud Data ◽  
Intensity Image

The unmanned aerial vehicle (UAV)-mounted mobile LiDAR system (ULS) is widely used for geomatics owing to its efficient data acquisition and convenient operation. However, due to limited carrying capacity of a UAV, sensors integrated in the ULS should be small and lightweight, which results in decrease in the density of the collected scanning points. This affects registration between image data and point cloud data. To address this issue, the authors propose a method for registering and fusing ULS sequence images and laser point clouds, wherein they convert the problem of registering point cloud data and image data into a problem of matching feature points between the two images. First, a point cloud is selected to produce an intensity image. Subsequently, the corresponding feature points of the intensity image and the optical image are matched, and exterior orientation parameters are solved using a collinear equation based on image position and orientation. Finally, the sequence images are fused with the laser point cloud, based on the Global Navigation Satellite System (GNSS) time index of the optical image, to generate a true color point cloud. The experimental results show the higher registration accuracy and fusion speed of the proposed method, thereby demonstrating its accuracy and effectiveness.

Automated Emission Data Registration and Segmentation for IC Analysis

2016 ◽  
Author(s):  
Franco Stellari ◽  
Peilin Song
Keyword(s):  
Data Analysis ◽  
Registration Accuracy ◽  
Emission Data ◽  
Data Registration ◽  
Different Types ◽  
Test Chips

Abstract In this paper, the development of advanced emission data analysis methodologies for IC debugging and characterization is discussed. Techniques for automated layout to emission registration and data segmentations are proposed and demonstrated using both 22 nm and 14 nm SOI test chips. In particular, gate level registration accuracy is leveraged to compare the emission of different types of gates and quickly create variability maps automatically.

scholarly journals Laparoscopic augmented reality registration for oncological resection site repair

2021 ◽  
Author(s):  
Fabian Joeres ◽  
Tonia Mielke ◽  
Christian Hansen
Keyword(s):  
Augmented Reality ◽  
Time Pressure ◽  
Tumour Resection ◽  
Anatomical Landmarks ◽  
Proof Of Concept ◽  
Registration Accuracy ◽  
Target Registration Error ◽  
Concept Evaluation ◽  
Navigation Support ◽  
Challenges And Opportunities

Abstract Purpose Resection site repair during laparoscopic oncological surgery (e.g. laparoscopic partial nephrectomy) poses some unique challenges and opportunities for augmented reality (AR) navigation support. This work introduces an AR registration workflow that addresses the time pressure that is present during resection site repair. Methods We propose a two-step registration process: the AR content is registered as accurately as possible prior to the tumour resection (the primary registration). This accurate registration is used to apply artificial fiducials to the physical organ and the virtual model. After the resection, these fiducials can be used for rapid re-registration (the secondary registration). We tested this pipeline in a simulated-use study with $$N=18$$ N = 18 participants. We compared the registration accuracy and speed for our method and for landmark-based registration as a reference. Results Acquisition of and, thereby, registration with the artificial fiducials were significantly faster than the initial use of anatomical landmarks. Our method also had a trend to be more accurate in cases in which the primary registration was successful. The accuracy loss between the elaborate primary registration and the rapid secondary registration could be quantified with a mean target registration error increase of 2.35 mm. Conclusion This work introduces a registration pipeline for AR navigation support during laparoscopic resection site repair and provides a successful proof-of-concept evaluation thereof. Our results indicate that the concept is better suited than landmark-based registration during this phase, but further work is required to demonstrate clinical suitability and applicability.

scholarly journals Detection of vessel bifurcations in CT scans for automatic objective assessment of deformable image registration accuracy

2021 ◽  
Author(s):  
Guillaume Cazoulat ◽  
Brian M Anderson ◽  
Molly M McCulloch ◽  
Bastien Rigaud ◽  
Eugene J Koay ◽  
...  
Keyword(s):  
Image Registration ◽  
Objective Assessment ◽  
Deformable Image Registration ◽  
Ct Scans ◽  
Registration Accuracy ◽  
Vessel Bifurcations

Reorienting the tibial baseplate improves the registration accuracy of model-based radiostereometric analysis

2020 ◽  
Vol 113 ◽  
pp. 110078
Author(s):  
Abigail E. Niesen ◽  
Anna L. Garverick ◽  
Stephen M. Howell ◽  
Maury L. Hull
Keyword(s):  
Radiostereometric Analysis ◽  
Registration Accuracy ◽  
Model Based

Improved Registration Accuracy in E-Beam Direct Writing Lithography

1993 ◽  
Vol 32 (Part 1, No. 12B) ◽  
pp. 6035-6038
Author(s):  
Yoshikatsu Kojima ◽  
Hiroshi Mukai ◽  
Ken Nakajima ◽  
Naoaki Aizaki
Keyword(s):  
Direct Writing ◽  
Registration Accuracy

scholarly journals Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
Kunlin Cao ◽  
Kai Ding ◽  
Joseph M. Reinhardt ◽  
Gary E. Christensen
Keyword(s):  
Cost Function ◽  
Human Subjects ◽  
Deformation Pattern ◽  
Jacobian Determinant ◽  
Registration Accuracy ◽  
Positioning Errors ◽  
Lung Motion ◽  
Volumetric Ct ◽  
Volumetric Registration ◽  
Vessel Tree

Accurate pulmonary image registration is a challenging problem when the lungs have a deformation with large distance. In this work, we present a nonrigid volumetric registration algorithm to track lung motion between a pair of intrasubject CT images acquired at different inflation levels and introduce a new vesselness similarity cost that improves intensity-only registration. Volumetric CT datasets from six human subjects were used in this study. The performance of four intensity-only registration algorithms was compared with and without adding the vesselness similarity cost function. Matching accuracy was evaluated using landmarks, vessel tree, and fissure planes. The Jacobian determinant of the transformation was used to reveal the deformation pattern of local parenchymal tissue. The average matching error for intensity-only registration methods was on the order of 1 mm at landmarks and 1.5 mm on fissure planes. After adding the vesselness preserving cost function, the landmark and fissure positioning errors decreased approximately by 25% and 30%, respectively. The vesselness cost function effectively helped improve the registration accuracy in regions near thoracic cage and near the diaphragm for all the intensity-only registration algorithms tested and also helped produce more consistent and more reliable patterns of regional tissue deformation.

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