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 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.

Implementation of Verification and Matching E-KTP with Faster R-CNN and ORB

2021 ◽  
Vol 5 (4) ◽  
pp. 783-793
Author(s):  
Muhammad Muttabi Hudaya ◽  
Siti Saadah ◽  
Hendy Irawan
Keyword(s):  
Image Matching ◽  
Nearest Neighbor ◽  
Feature Matching ◽  
Image Feature ◽  
Brute Force ◽  
K Nearest Neighbor ◽  
Matching Method ◽  
Average Precision ◽  
Detection Model ◽  
Matching Process

needs a solid validation that has verification and matching uploaded images. To solve this problem, this paper implementing a detection model using Faster R-CNN and a matching method using ORB (Oriented FAST and Rotated BRIEF) and KNN-BFM (K-Nearest Neighbor Brute Force Matcher). The goal of the implementations is to reach both an 80% mark of accuracy and prove matching using ORB only can be a replaced OCR technique. The implementation accuracy results in the detection model reach mAP (Mean Average Precision) of 94%. But, the matching process only achieves an accuracy of 43,46%. The matching process using only image feature matching underperforms the previous OCR technique but improves processing time from 4510ms to 60m). Image matching accuracy has proven to increase by using a high-quality dan high quantity dataset, extracting features on the important area of EKTP card images.

scholarly journals Image Matching Process on Images Taken by a Cellular Phone

2003 ◽  
Vol 57 (9) ◽  
pp. 1177-1186 ◽  
Author(s):  
Yi Hu ◽  
Tomoharu Nagao ◽  
Masanori Okazaki ◽  
Taishi Chinone
Keyword(s):  
Image Matching ◽  
Cellular Phone ◽  
Matching Process

scholarly journals OPTIMIZATION ALGORITHM OF TILTED IMAGE MATCHING BASED ON ADAPTIVE INITIAL OBJECT ASPECT

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 547-554
Author(s):  
C. Zhang ◽  
Y. Ge ◽  
Q. Zhang ◽  
B. Guo
Keyword(s):  
Least Squares ◽  
Image Matching ◽  
Normal Vector ◽  
Matching Method ◽  
Initial Value ◽  
Initial State ◽  
Matching Process ◽  
Low Degree ◽  
Verification Process ◽  
Initial Object

Abstract. When adopting the matching method of the least squares image based on object-patch to match tilted images, problems like the low degree of connection points for images with the discontinuity of depth or the discrepancy in elevation or low availability of aerotriangulation points would frequently appear. To address such problems, a tilted-image-matching algorithm based on an adaptive initial object-patch is proposed by this paper. By means of the existing initial values of the interior and exterior orientation elements of the tilted image and the information of object points generated in the matching process, the algorithm takes advantage of the method of multi-patch forward intersection and object variance partition so as to adaptively calculate the elevation of the object-patch and the initial value of the normal vector direction angle. Furthermore, this algorithm aims to solve the problem of difficulties in matching the tilted image with its corresponding points brought about by the low accuracy of the initial value of the tilted image when adopting the matching method of the least squares image based on object-patch to match the tilted image with high discrepancy in elevation. We adopt the algorithm as proposed in this paper and the least squares image matching method in which the initial state of the object-patch is horizontal to the object-patch respectively to conduct the verification process of comparing and matching two groups of tilted images. Finally, the effectiveness of the algorithm as proposed in this paper is verified by the testing results.

scholarly journals Intensity-Based 2D-3D Spine Image Registration Incorporating One Fiducial Marker

2003 ◽  
pp. 287-294 ◽  
Author(s):  
Daniel B. Russakoff ◽  
Torsten Rohlfing ◽  
Ramin Shahidi ◽  
Daniel H. Kim ◽  
John R. Adler ◽  
...  
Keyword(s):  
Image Registration ◽  
Fiducial Marker

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.

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