• Title/Summary/Keyword: Residual Dense Block

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Implant placement in severely atrophic mandible using alveolar ridge splitting procedure and small block bone graft: A case report of 4-year follow-up (심하게 위축된 하악 구치부에 치조제 분할술과 블록형 골이식술을 이용한 임플란트 식립: 4년 관찰 증례보고)

  • Kim, Na-Hong;Bang, Joo-Hyuk;Lee, Dong-Woon
    • Journal of the Korean Academy of Esthetic Dentistry
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    • v.28 no.2
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    • pp.64-73
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    • 2019
  • Various techniques have been developed, and the development of piezo electric devices have made it possible to widen the alveolar ridge even if the residual bone is dense or if there is a lack of cancellous bone between the cortical bones. In the operation of the mandibular posterior area, the flap is easily accessible to the ramus bone, from which high quality autogenous bone can be obtained, compared to other parts. A small autologous bone block can be used with particulated bone graft material using one screw for bone regeneration instead of a large autologous bone with two screws. The tapered implant design can minimize buccal bone fracture, even in severely atrophic mandibular areas. We report a case of 4 years following implant placement with ridge splitting and small autogenous bone graft in severly atrophic mandible. This report demonstrates a case of functional and aesthetic restoration in a patient through a collaboration.

Production of Single Core with Waste Zirconia Block (지르코니아 블록 폐기물을 이용한 싱글코어의 제조법)

  • Jo, Jun-Ho;Seo, Jeong-Il;Bae, Won-Tae
    • Journal of Technologic Dentistry
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    • v.35 no.1
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    • pp.57-64
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    • 2013
  • Purpose: Waste parts of zirconia blocks and powders were remained after CAD/CAM process. In order to make these residual zirconia fit for practical use, zirconia single cores were produced by drain casting process. Methods: Remained zirconia blocks were reduced to powders with zirconia mortar, and screened with 180 mesh sieve. Zirconia slip was prepared from waste parts of zirconia by ball milling. Plaster molds for forming cores by slip casting were also prepared. Formed cores were removed from mold after partial drying. Dried cores were biscuit fired at $1,100^{\circ}C$ for 1hour. Biscuit fired cores were treated with tools to control the fitness and thickness. Finished cores were $2^{nd}$ fired at $1,500^{\circ}C$ for 1hour. Microstructure of cross section of core was observed by SEM. Results: When mill pot was filled with 100g of zirconia and alumina mixed powder, 300g of zirconia ball, and 180g of distilled water, the optimum slip for drain casting was obtained. Gypsum plaster for ceramic forming was more suitable then yellow stone plaster for casting process. SEM photograph showed the microstructure of fully dense with uniform grain size of zirconia and well dispersed alumina grains into the zirconia matrix. Conclusion: Zirconia single cores were produced by drain casting process. Drain casting is useful process to make these residual zirconia fit for practical use. Further study will be focused on the preparation of the bridge type cores by casting.

Development of deep learning network based low-quality image enhancement techniques for improving foreign object detection performance (이물 객체 탐지 성능 개선을 위한 딥러닝 네트워크 기반 저품질 영상 개선 기법 개발)

  • Ki-Yeol Eom;Byeong-Seok Min
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.99-107
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    • 2024
  • Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.