Image analysis in ultrasonography using wavelet transform and its application to the diagnosis of Sjoegren's syndrome
| Project/Area Number |
26462843
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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 | Kyushu University |
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Principal Investigator |
Ohki Masafumi 九州大学, 医学研究院, 教授 (10160441)
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| Co-Investigator(Renkei-kenkyūsha) |
NAKAMURA Takashi 長崎大学, 大学院医歯薬学総合研究科, 教授 (30172406)
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| Research Collaborator |
MATSUI Takehiro
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2016: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | ウェーブレット変換 / シェーグレン症候群 / 超音波画像診断 / コンピュータ支援診断 / ウェーブレット解析 |
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| Outline of Final Research Achievements |
In this study, we aimed to develop an image analysis for improving diagnostic accuracy in ultrasonography, which is highly important as a noninvasive diagnosis of Sjoegren's syndrome. We developed an image analysis using dual tree complex wavelet transform (DT - CWT) and analyzed the parotid gland ultrasonographic images of 174 patients, including 77 cases who were considered positive for Sjoegren 's syndrome by sialography. As a result of the diagnostic accuracy combined with DT-CWT and machine learning, the sensitivity in the low severity group was 90 ± 3.7% and the accuracy was 88 ± 4.2%. The fact that the sensitivity was 79% and the accuracy was 80% by a dentist indicated the usefulness of this image analysis in clinical diagnosis.
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Report
(4 results)
Research Products
(5 results)
