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Developments of Computer Aided Diagnosis System of liver cancers using knowledge Engineering for Medical X-ray CT Images

Developments of Computer Aided Diagnosis System of liver cancers using knowledge Engineering for Medical X-ray CT Images
医学X射线CT图像知识工程肝癌计算机辅助诊断系统的研制
批准号:
21560428
负责人:
UENO Junji
金额:
$1.66万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
2009
资助国家:
日本
项目状态:
已结题
起止时间:
2009 至 2011

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中文摘要
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英文摘要
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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Feedback GMDH-type neural network and its application to medical image analysis of the liver cancer
反馈GMDH型神经网络及其在肝癌医学图像分析中的应用
DOI: --
发表时间: 2010
期刊: Abstracts of the 42^<nd> ISCIE international symposium on stochastic systems theory and its applications
影响因子: --
作者: [Tadashi Kondo, Junji Ueno]
通讯作者: Junji Ueno
Medical image diagnosis of liver cancer-using multi-layered GMDH-type neural network
肝癌的医学图像诊断——多层GMDH型神经网络
DOI: --
发表时间: 2010
期刊:
影响因子: --
作者: [Tadashi Kondo, Junji Ueno]
通讯作者: Junji Ueno
Medical Image Diagnosis of Liver Cancer by Multi-layered GMDH-type Neural Network Using Knowledge Base
基于知识库的多层GMDH型神经网络对肝癌的医学图像诊断
DOI: --
发表时间: 2012
期刊: ICIC Express Letters (ICIC-EL)
影响因子: --
作者: [Ryusuke Mayuzumi and Tetsuya Kojima, Yoshiya Horii and Tetsuya Kojima, 堀井与志也, Tadashi Kondo]
通讯作者: Tadashi Kondo
DOI: --
发表时间: 2009
期刊: The Journal of Artificial Life and Robotics Vol.14
影响因子: --
作者: [Masahiro Nakagawa, Tadashi Kondo, Kudo Tsuyosi, Shoichiro Takao and Junji Ueno, Nakagawa M.]
通讯作者: Nakagawa M.
17
    Medical image analysis of abdominal X-ray CT images by hybrid deep neural network of deep logistic GMDH-type neural network and convolutional neural network
    • 批准号:
      15K06145
    • 项目类别:
      Grant-in-Aid for Scientific Research (C)
    • 资助金额:
      $1.91万
    • 财政年份:
      2015
    • 负责人:
      UENO Junji
    • 依托单位:
    海外基金