FEATURE EXTRACTION AND CLASSIFICATION FOR HUMAN BRAIN CT IMAGES

摘要：

In this paper, Computer Aided Diagnosis (CAD) is applied to the brain CT image processing.In addition to the 3 classical types of features, i.e.gray scale, shape and texture, the symmetric feature based on the characteristics of human-brain CT image is extracted.Inductive learning techniques, See5 and RBFNN (Radial Basis Function of Nerve Network) are used to build classifiers for normal and abnormal brain CT images.Experimental results show that CAD system of human-brain CT image processing can assist doctors to correctly classify the CT images.

关键词： CAD Feature extraction Classification Medical image

作者: WEI-LI ZHANG XI-ZHAO WANG

作者单位: Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University, Baoding 071002, China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 1155-1159

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）