Individual tooth segmentation in human teeth images using deep neural networks심층신경망을 이용한 사람 치아 영상에서의 개별 치아 분할

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In human teeth images taken outside the oral cavity with a general digital camera, it is difficult to segment individual tooth due to common obstacles such as weak edges, intensity inhomogeneities and strong light reflections. In this work, we propose a method for segmenting individual tooth in human teeth images. The key to this method is to obtain pseudo edge-region using deep neural networks. We present a strategy for training neural networks while significantly simplifying the labeling process of training data using model-based methods. After an additional step to obtain initial contours for each tooth region, the individual tooth is segmented by applying active contour models.
Advisors
Lee, Chang-Ockresearcher이창옥researcher
Description
한국과학기술원 :수리과학과,
Publisher
한국과학기술원
Issue Date
2022
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 수리과학과, 2022.8,[v, 41 p. :]

Keywords

Image segmentation▼aTooth segmentation▼aNeural network▼aGeometric attraction-driven flow▼aEdge-region▼aLight reflection; 영상 분할▼a치아 분할▼a심층 신경망▼a기하적 유동▼a에지 영역▼a빛 반사

URI
http://hdl.handle.net/10203/308566
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1007824&flag=dissertation
Appears in Collection
MA-Theses_Ph.D.(박사논문)
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