• 대한의용생체공학회:의공학회지
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• 제9권2호
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• pp.153-158
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• 1988

A three-dimensional surface is reconstructed from contour information as identified on two-dimensional computed tomographic slices. Gradient operator with curvature constraint would be applied to extract the contour automatically, and backtracking is also adopted to reduce the tracking error. The surface between the consecutive slice is efficiently reconstructed using a triangular surface tiles. Hidden surface elimination, shading and parallel projection of the reconstructed surface are provied on the display screen.

• Journal of International Society for Simulation Surgery
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• 제2권2호
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• pp.67-70
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• 2015

We propose an automatic vessel segmentation method of vertebral arteries in CT angiography using combined circular and cylindrical model fitting. First, to generate multi-segmented volumes, whole volume is automatically divided into four segments by anatomical properties of bone structures along z-axis of head and neck. To define an optimal volume circumscribing vertebral arteries, anterior-posterior bounding and side boundaries are defined as initial extracted vessel region. Second, the initial vessel candidates are tracked using circular model fitting. Since boundaries of the vertebral arteries are ambiguous in case the arteries pass through the transverse foramen in the cervical vertebra, the circle model is extended along z-axis to cylinder model for considering additional vessel information of neighboring slices. Finally, the boundaries of the vertebral arteries are detected using graph-cut optimization. From the experiments, the proposed method provides accurate results without bone artifacts and eroded vessels in the cervical vertebra.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.277-278
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• 1998

CT/MRI images were frequently taken to evaluate the anatomic structure and disease status, and to plan the treatment modality for oral and maxillofacial surgery. However, surgeons have many difficulties in reading and understanding 2D images without long time experiences. This study presents the method of 3D reconstruction with fine CT slices and its clinical application. We applied this method a clinical patient with oral and maxillofacial trauma and produced 3D reconstructed model which shows the fracture line in panfacial area and bone defect.

• Nuclear Engineering and Technology
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• 제52권10호
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• pp.2313-2319
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• 2020

The goal of this project is to achieve an accurate segmentation of the pulmonary tumors besides shortening the time and increasing the accuracy. Here, improved region growing (IRG) algorithm is introduced in order to segment the lung tumor with a sufficient accuracy in a shorter time compared to the other basics methods. This comprehensive algorithm was applied on 4 patients CT images and the results of the various steps on segmentation improvement shown 98% accuracy as compared to the basic algorithm. The combination of "multipoint growth start" produced a desirable outcome in accurately bounding the tumor. The proposed algorithm improved tumor identification by less than 13% along with a sufficient percentage of compliance accuracy.

• The Journal of Advanced Prosthodontics
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• 제8권2호
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• pp.101-109
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• 2016

PURPOSE. To investigate the void parameters within the resin cements used for fiber post cementation by micro-CT (${\mu}CT$) and regional push-out bonding strength. MATERIALS AND METHODS. Twenty-one, single and round shaped roots were enlarged with a low-speed drill following by endodontic treatment. The roots were divided into three groups (n=7) and fiber posts were cemented with Maxcem Elite, Multilink N and Superbond C&B resin cements. Specimens were scanned using ${\mu}CT$ scanner at resolution of $13.7{\mu}m$. The number, area, and volume of voids between dentin and post were evaluated. A method of analysis based on the post segmentation was used, and coronal, middle and apical thirds considered separately. After the ${\mu}CT$ analysis, roots were embedded in epoxy resin and sectioned into 2 mm thick slices (63 sections in total). Push-out testing was performed with universal testing device at 0.5 mm/min cross-head speed. Data were analyzed with Kruskal-Wallis and Mann-Whitney U tests (${\alpha}=.05$). RESULTS. Overall, significant differences between the resin cements and the post level were observed in the void number, area, and volume (P<.05). Super-Bond C&B showed the most void formation ($44.86{\pm}22.71$). Multilink N showed the least void surface ($3.51{\pm}2.24mm^2$) and volume ($0.01{\pm}0.01mm^3$). Regional push-out bond strength of the cements was not different (P>.05). CONCLUSION. ${\mu}CT$ proved to be a powerful non-destructive 3D analysis tool for visualizing the void parameters. Multilink N had the lowest void parameters. When efficiency of all cements was evaluated, direct relationship between the post region and push-out bonding strength was not observed.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.285-286
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• 1998

Virtual Brain-endoscopy is an effective method to detect lesion in brain. Brain is the most part of the human and is not easy part to operate so that reconstructing in 3D may be very helpful to doctors. In this paper, it is suggested that to increase the reliability, method of matching 3D object with the 2D CT slice. 3D Brain-endoscopy is reconstructed with 35 slices of 2D CT images. There is a plate in 3D brain-endoscopy so as to drag upward or downward to match the relevant 2D CT image. Relevant CT image guides the user to recognize the exact part he or she is investigating. VRML Script is used to make the change in images and PlaneSensor node is used to transmit the y coordinate value with the CT image. The result is test on the PC which has the following spec. 400MHz Clock-speed, 512MB ram, and FireGL 3000 3D accelerator is set up. The VRML file size is 3.83MB. There was no delay in controlling the 3D world and no collision in changing the CT images. This brain-endoscopy can be also put to practical use on medical education through internet.

• 한국방사선학회논문지
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• 제15권2호
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• pp.101-108
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• 2021

CT는 인체 내 장기의 해부학적 구조를 정확하게 나타낼 수 있으며, 영상의 분해능이 우수하다. Brain CT 검사 시 수정체의 방사선 감수성이 높아서 피폭의 영향을 많이 받는다. 본 연구는 수정체에 피폭선량을 감소하기 위해 비스무스와 텅스텐 필라멘트 차폐물질을 사용하여 Non-shield와 Shield에 대한 피폭선량의 변화와 차폐율을 비교 하고자 한다. 본 연구에서는 3D printing으로 제작한 비스무스, 텅스텐 필라멘트 차폐물질을 사용하여, 차폐물질 두께와 slice에 따라 피폭되는 선량을 측정하였다. 헤드팬텀을 고정시켜 안구에 Magicmax universal 선량계를 위치시켜 차폐 물질을 놓지 않았을 경우와 그 위에 차폐 물질을 놓았을 때 차폐율을 각각 비교하기 위해 두 물질을 1mm ~ 5mm 두께로 각각 측정하였다. 1 mm 두께의 필라멘트에서 비스무스 필라멘트는 26.8 %, 텅스텐 필라멘트는 43.1 % 차폐율이 나타났다. 따라서 비스무스 필라멘트보다 텅스텐 필라멘트에서 더 큰 차폐효과가 나타났다. 차폐체의 종류, 두께, 슬라이스 간격에 따라 선량을 측정한 결과, 비스무스 필라멘트 보다 텅스텐 필라멘트가 더 큰 차폐효과가 나타났다.

• 한국정보통신학회논문지
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• 제12권11호
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• pp.2077-2082
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• 2008

최근 MRI와 CT와 같은 의료영상에서의 진보한 기술은 의사들에게 상세한 해부학적 정보를 제공하게 하여 그들의 진단 능력을 향상시키고 있다. 일반적으로 보다 상세한 정보를 얻기 위해서는 많은 수의 MRI이미지를 필요로 한다. 그러나 일반 병원에서 접하는 MRI 기계의 성능이 우수하지 않은 경우가 많고 따라서 획득되는 이미지의 수가 적다. 결과적으로 적은 수의 슬라이스를 이용해 3D surface를 재구성하게 되면 퀄리티가 낮아지는 문제가 발생한다. 본 논문에서는 적은 수의 슬라이스를 이용하여 높은 퀄리티의 3D surface를 얻는 방법을 제안한다. 이를 위한 알고리즘은 먼저 원하는 영역의 경계를 찾아서 그 경계선들의 점을 찾는다. 이러한 점들로부터 Radial Basis Function을 이용해서 점들을 모두 지나는 음함수 곡면 수식을 생성한다. 생성된 음함수 곡면수식으로부터 Marching cube 알고리즘을 이용하여 렌더링 한다.

• Advances in nano research
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• 제12권2호
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• pp.185-195
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• 2022

Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.

• 치과방사선
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• 제27권1호
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• pp.7-16
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• 1997

This study was performed to demonstrate the method of image reformation for dental implants, using a personal computer with inexpensive softwares and to compare the images reformatted using the above method with those using Dentascan software. CT axial slices of 5 mandibles of 5 volunteers from GE Highspeed Advantage(GE Medical systems, U.S.A.) were used. Personal computer used for image reformation was PowerWave 6041120 (Power Computing Co, U.S.A.) and softwares used were Osiris (Univ. Hospital of Geneva, Switzerland) and Import ACCESS V1.H Designed Access Co., U.S.A.) for importing CT images and NIH Image 1.58 (NIH, U.S.A.) for image processing. Seven images were selected among the serial reconstructed cross-sectional images produced by Dentascan(DS group). Seven resliced cross-sectional images at the same position were obtained at the personal computer(PC group). Regression analysis of the measurements of PC group was done against those of DS group. Measurements of the bone height and width at the reformed cross-sectional images using Mac-compatible computer were highly correlated with those using workstation with Dentascan software(height : r²=0.999, p<0.001, width : r²=0.991, p<0.001). So, it is considered that we can use a personal computer with inexpensive softwares for the dental implant planning, instead of the expensive software and workstation.