• Imaging Science in Dentistry
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• v.42 no.3
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• pp.139-146
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• 2012

Purpose: An individual surgical stent fabricated from computed tomography (CT) data, called a CT-guided stent, would be useful for accurate installation of implants. The purpose of the present study was to introduce a newly developed CT-guided stent with a simple design and evaluate the accuracy of the stent placement. Materials and Methods: A resin template was fabricated from a hog mandible and a specially designed plastic plate, with 4 metal balls inserted in it for radiographic recognition, was attached to the occlusal surface of the template. With the surgical stent applied, CT images were taken, and virtual implants were placed using software. The spatial positions of the virtually positioned implants were acquired and implant guiding holes were drilled into the surgical stent using a specially designed 5-axis drilling machine. The surgical stent was placed on the mandible and CT images were taken again. The discrepancy between the central axis of the drilled holes on the second CT images and the virtually installed implants on the first CT images was evaluated. Results: The deviation of the entry point and angulation of the central axis in the reference plane were $0.47{\pm}0.27$ mm, $0.57{\pm}0.23$ mm, and $0.64{\pm}0.16^{\circ}$, $0.57{\pm}0.15^{\circ}$, respectively. However, for the two different angulations in each group, the $20^{\circ}$ angulation showed a greater error in the deviation of the entry point than did the $10^{\circ}$ angulation. Conclusion: The CT-guided template proposed in this study was highly accurate. It could replace existing implant guide systems to reduce costs and effort.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.73-83
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• 2009

In this paper we propose an object similarity matching method based on shape characteristics of an object in an image. The proposed method extracts edge points from edges of objects and generates a log polar histogram with respect to each edge point to represent the relative placement of extracted points. It performs the matching in such a way that it compares polar histograms of two edge points sequentially along with edges of objects, and uses a well-known k-NN(nearest neighbor) approach to retrieve similar objects from a database. To verify the proposed method, we've compared it to an existing Shape-Context method. Experimental results reveal that our method is more accurate in object matching than the existing method, showing that when k=5, the precision of our method is 0.75-0.90 while that of the existing one is 0.37, and when k=10, the precision of our method is 0.61-0.80 while that of the existing one is 0.31. In the experiment of rotational transformation, our method is also more robust compared to the existing one, showing that the precision of our method is 0.69 while that of the existing one is 0.30.

• Smart Media Journal
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• v.9 no.4
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• pp.102-108
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• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.