| Project/Area Number |
21560428
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
System engineering
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| Research Institution | The University of Tokushima |
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Principal Investigator |
UENO Junji 徳島大学, 大学院・ヘルスバイオサイエンス研究部, 教授 (60116788)
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| Co-Investigator(Kenkyū-buntansha) |
KONDO Tadashi 徳島大学, 大学院・ヘルスバイオサイエンス研究部, 教授 (80205559)
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2010: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2009: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | システム情報(知識)処理 / 人工ニューラルネットワーク / コンピュータ支援診断 / 知識工学 / マルチスライスCT / システム情報処理 / CT / 肝臓癌 |
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| Research Abstract |
A revised Group Method of Data Handling(GMDH)-type neural network algorithm for medical image diagnosis is proposed and is applied to medical image diagnosis of liver cancer that is called hepatocellular carcinoma(HCC). In this algorithm, the knowledge base for medical image diagnosis are used for organizing the neural network architecture for medical image diagnosis and the revised GMDH-type neural network algorithm can identify the characteristics of the medical images accurately. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares(PSS) and it was shown that the revised GMDH-type neural network could be easily applied to the medical image diagnosis.
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