| Project/Area Number |
16K11615
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Prosthodontics/ Dental materials science and
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| Research Institution | Tsurumi University |
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Principal Investigator |
IKAWA TOMOKO 鶴見大学, 歯学部, 助教 (70552389)
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| Co-Investigator(Kenkyū-buntansha) |
小川 匠 鶴見大学, 歯学部, 教授 (20267537)
重田 優子 鶴見大学, 歯学部, 講師 (40367298)
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| Research Collaborator |
Otake Yoshito
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2016: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
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| Keywords | 計算解剖学 / CADCAMシステム / デジタルデンティストリー / セグメンテーション / 統計アトラス / CAD／CAMシステム |
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| Outline of Final Research Achievements |
The segmentation of musculoskeletal structures, e.g. masseter muscle and mandible, in computed tomography (CT) images is important for the diagnosis and treatment planning of maxillofacial disorders.However, the presence of a metal prosthesis, such as dental fillings, leads to metal artifacts in the CT images that degrade the segmentation accuracy.In our previous study, we developed a musculoskeletal segmentation method applied to metal artifact-reduced CT images and evaluated it based on the manual trace produced from metal artifact-reduced CT images.In this research, instead, we simulated metal artifacts in the CT images and evaluated the segmentation accuracy using labels produced from CT images without metal artifact.In addition, we proposed an improvement of the conventional Normalized Metal Artifact Reduction (NMAR) method, and compared the impact of three metal artifact reduction methods on the segmentation accuracy.
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| Academic Significance and Societal Importance of the Research Achievements |
歯科補綴は，補綴装置により欠損した顔面形態，顎骨や歯を補い機能を回復することにあるが，その環境は様々であり，固有の形態に合致し，良好な機能を回復することは難しい．本研究では，顎顔面頭蓋や歯列，歯の形態の様々なデジタル情報を用いて統計解析（計算解剖学的手法）を行うことにより患者個別に最適な解剖学的形態を算出，CAD/CAM技術に応用し，機能に即した顎顔面補綴装置や口腔内の修復装置を設計・製作することが目的である．これは個々に存在している多種多様な情報を効果的（有機的）に統合する手法であり，様々な研究へ展開可能である．
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