지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.5
- 수록면
- 39 - 44 (6page)
이용수
초록· 키워드
오류제보하기
The AI technology has been insistently integrated into diverse fields to assist human activities in the modern world. Owing to its excellent job, we observe the benefits of applying this technology to dentistry. In this paper, we present an AI-based approach for dental prostheses fabrication to reduce manual effort associated with the process, particularly in crowns design. Technically, we propose a Pix2Pix model to automatically generate crowns image for damaged teeth, instead of relying on handcrafted drawing. Pix2Pix is remarkable for image-to-image translation applications whose model structure is based on a conditional GAN. Our proposed framework produced satisfactory results, both qualitatively and quantitatively, despite having small teeth image datasets, demonstrating 0.0012, 0.9689, and 34.91 for MSE, SSIM, and PSNR, respectively.
목차
ABSTRACT
1. Introduction
2. Related Work
3. Method
4. Results
5. Future Works
References
참고문헌 (16)
참고문헌 신청
Martelli A / 1976 / An application of heuristic search methods to edge and contour detection / Commun Acm 19:73~83
Chakraborty A / 1995 / On multi-feature inte-gration for deformable boundary finding / Ieee I Conf Comp Vis :846~851
Milletari F / 2016 / V-net: Fully convolutional neural networks for volumetric medical image segmentation / IEEE Int’l Conf. on 3D vision (3DV):565~565
Drozdzal M / 2016 / Deep learning and data labeling for medical applica-tions / Springer :179~187
Shlafman S / 2002 / Computer Graphics Forum / Blackwell Publishing, Inc :219~228
Chakraborty A / 1995 / On multi-feature inte-gration for deformable boundary finding / Ieee I Conf Comp Vis :846~851
Milletari F / 2016 / V-net: Fully convolutional neural networks for volumetric medical image segmentation / IEEE Int’l Conf. on 3D vision (3DV):565~565
Drozdzal M / 2016 / Deep learning and data labeling for medical applica-tions / Springer :179~187
Shlafman S / 2002 / Computer Graphics Forum / Blackwell Publishing, Inc :219~228
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