计算机科学与探索2018，Vol.12Issue(4)：608-617,10.DOI:10.3778/j.issn.1673-9418.1704042
结合卷积神经网络和模糊系统的脑肿瘤分割
Brain Tumor Image Segmentation Algorithm Based on Convolution Neural Net-work and Fuzzy Inference System
摘要
Abstract
In order to improve the accuracy and robustness of brain tumor image segmentation,this paper proposes an automatic segmentation algorithm of brain tumor MRI image based on convolution neural network and fuzzy inference system. Firstly, the convolution neural networks for the two types of single mode images of FLAIR and T2 are constructed.Then,the corresponding convolution neural network model is applied to each type of images to obtain the predicted probability which is processed by nonlinear mapping.Finally,the nonlinear mapped probability of the two kinds of images of FLAIR and T2 is used as the input of fuzzy inference system to determine whether the pixel belongs to the tumor area.Compared with existing brain tumor MRI image segmentation algorithm,the experi-mental results show that the proposed algorithm has an improvement in segmentation accuracy.关键词
脑肿瘤/图像分割/卷积神经网络/模糊推理系统Key words
brain tumor/image segmentation/convolution neural network/fuzzy inference system分类
信息技术与安全科学引用本文复制引用
师冬丽,李锵,关欣..结合卷积神经网络和模糊系统的脑肿瘤分割[J].计算机科学与探索,2018,12(4):608-617,10.基金项目
The National Natural Science Foundation of China under Grant No.61471263(国家自然科学基金) （国家自然科学基金）
the Natural Science Foundation of Tianjin under Grant No.16JCZDJC31100(天津市自然科学基金). （天津市自然科学基金）
