• 한국방사선학회논문지
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• 제7권4호
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• pp.301-305
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• 2013

Cone Beam CT 데이터를 3차원 컴퓨터 프로그램을 이용하여 기존의 파노라마 영상과 재구성된 파노라마 영상을 재현해서 악궁형태에 따른 치아의 왜곡을 분석하고자 하였다. Cone Beam CT의 횡단면 영상과 재구성 파노라마에서 측정된 치아의 직경은 전치부에서 구치부로 갈수록 큰 변화없이 일치되는 것을 알 수 있었다. 하지만 파노라마는 전치부에서 약간의 왜곡이 보이다가 구치부로 갈수록 왜곡이 더 심한 것을 알 수 있었다. 환자 개개인의 악궁에 맞게 재구성된 파노라마가 일반적으로 사용되는 파노라마 촬영보다 왜곡이 더 감소한다는 것을 알 수 있었다. 또한 파노라마는 전치부에서 구치부로 갈수록 왜곡이 더 심해지는 것을 알 수 있었는데, 이 또한 재구성된 파노라마 영상에서는 왜곡이 감소한다는 것을 알 수 있었다.

• 한국컴퓨터정보학회논문지
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• 제23권4호
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• pp.57-64
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• 2018

In this paper, we propose the automatic detection method for individual region separation using panorama image. Finding areas that contain individual teeth is one of the most important tasks in automating 3D models through individual tooth separation. In the conventional method, the maxillary and mandibular teeth regions are separated using a straight line or a specific CT slide, and the tooth regions are separated using a straight line in the vertical direction. In the conventional method, since the teeth are arranged in a curved shape, there is a problem that each tooth region is incorrectly detected in order to generate an accurate tooth region. This is a major obstacle to automating the creation of individual tooth models. In this study, we propose a method to find the correct tooth curve by using the jawbone curve which is very similar to the tooth curve in order to overcome the problem of finding the area containing the existing tooth. We have proposed a new method to accurately set individual tooth regions using the feature that individual teeth are arranged in a direction similar to the normal direction of the tooth alignment curve. In the proposed method, the maxillary and mandibular teeth can be more precisely separated than the conventional method, and the area including the individual teeth can be accurately set. Experiments using real dental CT images demonstrate the superiority of the proposed method.

• 한국컴퓨터정보학회논문지
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• 제23권3호
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• pp.17-23
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• 2018

In this paper, we propose the automatic detection method which find the middle part of tooth crown to start individual tooth segmentation. There have been many studies on the automation of individual tooth segmentation, but there are still many problems for full automation. Detection of middle part of tooth crown used as initial information for individual tooth segmentation is closely related to performance, but most studies are based on the assumption that they are already known or they can be represented by using a straight line. In this study, we have found that the jawbone curve is similar to the tooth alignment curve by spatially analyzing the CT image, and propose a method to automatically detect the middle part of tooth crown. The proposed method successfully uses the jawbone curves to successfully create a tooth alignment curve that is difficult to detect. As the middle part of tooth crown is in the form of a tooth alignment curve, the proposed method detects the middle part of tooth crown successfully. It has also been verified by experiments that the proposed method works well on real dental CT images.

• 대한치과마취과학회지
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• 제9권1호
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• pp.24-29
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• 2009

When performing the inferior alveolar nerve block anesthesia, surgeon often faced a difficulty of the surgical operation due to the incomplete anesthesia. One of the reason is the variety of mandibular canal anatomy. Up to now, there are some reports of index cases about bifid mandibular canal among mandibular canal anatomic variation, and some classification is applied according to anatomical location and configuration. When surgical operation is performed involving mandible such as dantal implant treatment, extraction of an impacted third molar, sagittal split ramus osteotomy, etc, the position of mandibular canal should be considered. Bifid mandibular canal clinically causes troublesome cases of anesthesia when inferior alvelor nerve block, especially is performed extraction of an impacted third molar. Therefore, It is important for clinicians to recognize the presence of bifid canals on radiographys. Nowadays, the position of mandibular canal can be measured precisely by using Dental CT. It is not found by panorama image but is found by Dental CT sometimes. Among the patients, which take panorama and Dental CT simultaneously, for tooth extraction of lower impacted third molar in our department, we report the case that did not identifying in panorama but identifying it in Dental CT.