2014 Fiscal Year Final Research Report
Statistical iterative reconstruction for streak artefact reduction when using multi-detector CT to image the dento-alveolar structures
| Project/Area Number |
24592825
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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 |
Pathobiological dentistry/Dental radiology
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| Research Institution | Kitami Institute of Technology |
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Principal Investigator |
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| Research Collaborator |
KOBER Cornelia Biomechanics and Technical Mechanics, Faculty of Life Sciences, Hamburg University of Applied Sciences, Hamburg, Germany, Professor
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Keywords | 統計的画像再構成法 / 逐次近似法 / 歯顎顔面画像診断 / Ｘ線ＣＴ / 金属アーチファクト / 歯科放射線画像診断 / ストリーク・アーチファクト |
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| Outline of Final Research Achievements |
The objective was to reduce metal-induced streak artifact on oral and maxillofacial X-ray MDCT images by developing the fast statistical image reconstruction algorithm. When metallic prosthetic appliances exist in the oral cavity, the appearance of metal-induced streak artefacts is not avoidable. Adjacent CT images often depict similar anatomical structures in thin slices. Images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. The maximum likelihood-expectation maximization algorithm was applied. Next, the ordered subset-expectation maximization was examined. A small region of interest setting was designated. A GPGPU machine and CUDA programming were applied. Algorithms reduced metal-induced artifacts using the sequential processing method. The GPGPU realized the high performance. The CBCT image quality improved in combination with the 3D Gaussian-Laplacian filtering and region growing methods.
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| Free Research Field |
歯学，医用画像工学，医学物理学，放射線技術学，画像認識，画像解析，医療情報
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