Multi-objective differential evolution-based ensemble method for brain tumour diagnosis

著录项

• 来源
  《Image Processing, IET》 |2019年第9期|1421-1430|共10页
• 作者

  Rezaei Kimia; Agahi Hamed; Mahmoodzadeh Azar;

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• 作者单位

  Islamic Azad Univ Shiraz Branch Dept Elect Engn Shiraz Iran;

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• 收录信息
• 原文格式 PDF
• 正文语种 eng
• 中图分类
• 关键词

  medical image processing; brain; cancer; genetic algorithms; image classification; image texture; feature extraction; statistical analysis; tumours; multilayer perceptrons; computerised tomography; support vector machines; image segmentation; image denoising; image reconstruction; multiobjective differential evolution-based ensemble method; brain tumour diagnosis; tumour type; paramount issue; benign tumour slices; malignant tumour slices; tomography images; image reconstruction; mixed noise removal; weighted encoding; nonlocal regularisation technique; segmentation purpose; support vector machine; CT images; genetic algorithm; multilayer perceptron neural network; weighted kernel width SVM; nearest neighbours models; tumour classification phase; classification performance indices; weighted linear combination; objective functions; multistep method;

  机译：医学图像处理;脑;癌症;遗传算法;图像分类;图像纹理特征提取;统计分析;肿瘤多层感知器电脑断层扫描支持向量机;图像分割图像降噪影像重建;基于多目标差分进化的集成方法脑肿瘤诊断;肿瘤类型最重要的问题良性肿瘤切片;恶性肿瘤切片;断层图像;影像重建;混合噪声去除;加权编码;非局部正则化技术;分割目的;支持向量机CT图像;遗传算法多层感知器神经网络加权核宽度支持向量机;最近邻居模型;肿瘤分类阶段;分类性能指标;加权线性组合;目标功能;多步法;