Comparison of the Accuracy of Image Registration Methods for Merging Optical Scan and Radiographic Data in Edentulous Jaws

2020 ◽  
Vol 29 (8) ◽  
pp. 707-711
Author(s):  
Hyun‐Wook Woo ◽  
Hang‐Nga Mai ◽  
Du‐Hyeong Lee
Keyword(s):  
Image Registration ◽  
Optical Scan ◽  
Radiographic Data ◽  
Edentulous Jaws

Radiopaque Tissue Surface-Based Digital Registration Technique for Completely Edentulous Ridge

2020 ◽  
Author(s):  
Hang-Nga Mai ◽  
Du-Hyeong Lee
Keyword(s):  
Image Registration ◽  
Image Matching ◽  
Fiducial Marker ◽  
Surgical Guide ◽  
Matching Process ◽  
Optical Scan ◽  
Tissue Surface ◽  
Natural Teeth ◽  
Image Reversal ◽  
Radiographic Data

An accurate image registration of the optical scan of a completely edentulous ridge to radiographic data remains challenging due to the absence of natural teeth. This article introduces a radiopaque tissue surface-based digital registration technique that enhances the accuracy of the image matching process and improves the fit accuracy of the implant surgical guide. In this workflow, a radiopaque impression body that is the replica of the edentulous ridge was used as a surface-based fiducial marker for accurate image registration between the soft and hard tissues of a completely edentulous arch. A virtual edentulous model was generated by direct digitization of the impression body and a digital image reversal technique without the need for stone cast fabrication or additional intraoral scanning. The fabricated surgical guide showed close adaptation to the edentulous ridge of the patient.

scholarly journals Impacts of Thresholds of Gray Value for Cone-Beam Computed Tomography 3D Reconstruction on the Accuracy of Image Matching with Optical Scan

2020 ◽  
Vol 17 (17) ◽  
pp. 6375 ◽  
Author(s):  
Se-Won Park ◽  
Ra Gyoung Yoon ◽  
Hyunwoo Lee ◽  
Heon-Jin Lee ◽  
Yong-Do Choi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Registration ◽  
3D Reconstruction ◽  
Cone Beam Computed Tomography ◽  
Cone Beam ◽  
Dental Arch ◽  
Arch Model ◽  
3D Mesh ◽  
Optical Scan ◽  
Reconstruction Model

In cone-beam computed tomography (CBCT), the minimum threshold of the gray value of segmentation is set to convert the CBCT images to the 3D mesh reconstruction model. This study aimed to assess the accuracy of image registration of optical scans to 3D CBCT reconstructions created by different thresholds of grey values of segmentation in partial edentulous jaw conditions. CBCT of a dentate jaw was reconstructed to 3D mesh models using three different thresholds of gray value (−500, 500, and 1500), and three partially edentulous models with different numbers of remaining teeth (4, 8, and 12) were made from each 3D reconstruction model. To merge CBCT and optical scan data, optical scan images were registered to respective 3D reconstruction CBCT images using a point-based best-fit algorithm. The accuracy of image registration was assessed by measuring the positional deviation between the matched 3D images. The Kruskal–Wallis test and a post hoc Mann–Whitney U test with Bonferroni correction were used to compare the results between groups (α = 0.05). The correlations between the experimental factors were calculated using the two-way analysis of variance test. The positional deviations were lowest with the threshold of 500, followed by the threshold of 1500, and then −500. A significant interaction was found between the threshold of gray values and the number of remaining teeth on the registration accuracy. The most significant deviation was observed in the arch model with four teeth reconstructed with a gray-value threshold of −500. The threshold for the gray value of CBCT segmentation affects the accuracy of image registration of optical scans to the 3D reconstruction model of CBCT. The appropriate gray value that can visualize the anatomical structure should be set, especially when few teeth remain in the dental arch.

scholarly journals Impact of Matching Point Selections on Image Registration Accuracy between Optical Scan and Computed Tomography

2020 ◽  
Vol 2020 ◽  
pp. 1-7 ◽  
Author(s):  
Hai Yen Mai ◽  
Du-Hyeong Lee
Keyword(s):  
Computed Tomography ◽  
Image Registration ◽  
Image Matching ◽  
Surface Registration ◽  
Point Selection ◽  
Point Distribution ◽  
Registration Method ◽  
Planning Software ◽  
Optical Scan ◽  
Software Programs

The point-based surface registration method involves the manual selection process of paired matching points on the data of computed tomography and optical scan. The purpose of this study was to investigate the impact of selection error and distribution of fiducial points on the accuracy of image matching between 3-dimensional (3D) images in dental planning software programs. Computed tomography and optical scan images of a partial edentulous dental arch were obtained. Image registration of the optical scan image to computed tomography was performed using the point-based surface registration method in planning software programs under different conditions of 3 fiducial points: point selection error (0, 1, or 2 mm), point distribution (unilateral, bilateral), and planning software (Implant Studio, Blue Bio Plan) (n=5 per condition, N=60). The accuracy of image registration at each condition was evaluated by measuring linear discrepancies between matched images at X, Y, and Z axes. Kruskal-Wallis test, Mann-Whitney U test with Bonferroni correction, and 3-way analysis of variance were used to statistically analyse the measurement data (α=0.05). No statistically significant difference was exhibited between the 0 and 1 mm point mismatch conditions in either unilateral or bilateral point distributions. The discrepancy values in the 2 mm mismatch condition were significantly different from the other mismatch conditions, especially in the unilateral point distribution (P<0.05). Strong interactions among point selection error, distribution, and software programs on the image registration were found (P<0.001). Minor matching point selection error did not influence the accuracy of point-based automatic image registration in the software programs. When the fiducial points are distributed unilaterally with large point selection error, the image matching accuracy could be decreased.

scholarly journals Effects of Exposure Parameters and Voxel Size for Cone-Beam Computed Tomography on the Image Matching Accuracy with an Optical Dental Scan Image: An In Vitro Study

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Hang-Nga Mai ◽  
Du-Hyeong Lee
Keyword(s):  
Computed Tomography ◽  
Image Registration ◽  
Cone Beam Computed Tomography ◽  
Image Matching ◽  
Cone Beam ◽  
Matching Accuracy ◽  
Tube Voltage ◽  
Voxel Size ◽  
Optical Scan ◽  
Tube Current

This study is aimed at assessing the effects of exposure parameters and voxel size for cone-beam computed tomography (CBCT) on the image matching accuracy with an optical dental scan image. CBCT and optical scan images of a dry human mandible were obtained. Different CBCT settings were used: tube voltage, 60, 80, and 100 kVp; tube current, 6 and 8 mA; and voxel size, 100, 200, and 300 μm. Image matching between the CBCT and optical scan images was performed using implant planning software by dental professionals ( n = 18 ). The image matching accuracy in each combination of CBCT settings was evaluated by assessing the linear discrepancy between the three-dimensionally reconstructed radiological image and the registered optical scan image using an image analysis software program. The Kruskal-Wallis test and a post hoc Mann–Whitney U test with Bonferroni correction were used to compare the accuracy of image registration between the groups ( α = 0.05 ). Overall, the image matching accuracy was not significantly different between tube voltage and current settings; however, significantly higher image registration errors were found at the combination of 100 kVp tube voltage/8 mA tube current ( F = 8.44 , P < 0.001 ). Changes in voxel sizes did not significantly interfere with the image registration results. No interaction was found among voltage, current, and voxel size in terms of image registration accuracy ( F = 2.022 , P = 0.091 ). Different exposure parameter settings in tube voltage and tube current did not significantly influence the image matching accuracy between CBCT and optical dental scan images; however, a high radiation dose could be inappropriate. The image matching accuracy was not significantly affected by changing the voxel sizes of CBCT.

Comparative study of NOTES alone vs. NOTES guided by a new image registration system for navigation in the mediastinum: A study in a porcine model

Endoscopy ◽  
2012 ◽  
Vol 44 (10) ◽  
Author(s):  
H Córdova ◽  
R San José Estépar ◽  
A Rodríguez-D'Jesús ◽  
G Martínez-Pallí ◽  
P Arguis ◽  
...  
Keyword(s):  
Image Registration ◽  
Comparative Study ◽  
Porcine Model ◽  
Registration System

Improved 3D Scene Modeling for Image Registration in Change Detection

2019 ◽  
Vol 2019 (7) ◽  
pp. 465-1-465-7
Author(s):  
Sjors van Riel ◽  
Dennis van de Wouw ◽  
Peter de With
Keyword(s):  
Image Registration ◽  
Change Detection ◽  
Scene Modeling ◽  
3D Scene

Development of New Image Registration Techniques – A Research Framework

2018 ◽  
Vol 8 (3) ◽  
pp. 50
Author(s):  
Sindhu Madhuri G. ◽  
Indira Gandhi M P
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Digital Image Processing ◽  
Digital Image ◽  
Creative Thinking ◽  
Reference Image ◽  
Transformation Technique ◽  
Research Framework ◽  
Registration Process ◽  
Data Source

Image is a basic and fundamental data source for the digital image processing. This image data source is required to be processed into information or intelligence and further to knowledge levels where it is required to understand and migrate into knowledge economy systems. Image registration is one of such key and most important process already identified in the digital image processing domain. Image registration is a process of bringing the reference image and sensed image into a common co-ordinate system, and application of complex transformation techniques for necessary comparison of reference with sensed images obtained from different - views, times, spaces, etc., in order to extract the valuable information and intelligence embedded in them. Due to the complexity of overall image registration process, it is difficult to suggest a single transformation technique even for a specific application. In addition, it is highly impossible to suggest one single transformation technique for comparison of various sensed images with a reference image during the image registration process. This research gap calls for the development of new image registration techniques for the application of more than one transformation technique during the image registration process for the necessary comparisons with reference image & sensed images, those are obtained from the available heterogeneous sources or sensors, based on the requirement. In addition, it is a basic need to attempt for the measurement of effectiveness of the image registration process also. Therefore, a research framework is developed for image registration process and attempted for the measurement of its effectiveness also. This new research area is a novel idea, and is expected to emerge as a provision for the knowledge computations with creative thinking through the embedded intelligence extraction during the complex image registration process.

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