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

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dc.contributor.advisorLee, Chang-Ock-
dc.contributor.advisor이창옥-
dc.contributor.authorKim, Seongeun-
dc.date.accessioned2023-06-22T19:33:50Z-
dc.date.available2023-06-22T19:33:50Z-
dc.date.issued2022-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1007824&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/308566-
dc.description학위논문(박사) - 한국과학기술원 : 수리과학과, 2022.8,[v, 41 p. :]-
dc.description.abstractIn 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.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectImage segmentation▼aTooth segmentation▼aNeural network▼aGeometric attraction-driven flow▼aEdge-region▼aLight reflection-
dc.subject영상 분할▼a치아 분할▼a심층 신경망▼a기하적 유동▼a에지 영역▼a빛 반사-
dc.titleIndividual tooth segmentation in human teeth images using deep neural networks-
dc.title.alternative심층신경망을 이용한 사람 치아 영상에서의 개별 치아 분할-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :수리과학과,-
dc.contributor.alternativeauthor김성은-
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