an optimization classification algorithm for MRI images of premature brain injury is introduced. Based on the shortcomings of the classical ID3 algorithm in dealing with the continuous attributes of medical image, the new algorithm selects the testing feature by comparing the information gain ratio and adds the handling methods for filling null values. Then it discrete the continuous attributes by dividing them into segments to classify the object. The result shows that the new algorithm can accurately classify the MRI images
基金：
Hebei Province Key project of
medical science research (No.20150480).
语种：
外文
被引次数：
WOS：
第一作者：
第一作者机构：[1]Affiliated Hosp Hebei Univ, Baoding 071001, Hebei, Peoples R China
通讯作者：
推荐引用方式(GB/T 7714)：
Wang yu,Yang Xiaowei.Application of Decision Tree for MRI Images of Premature Brain Injury Classification[J].2016 11TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE).2016,792-795.doi:10.1109/ICCSE.2016.7581683.
APA：
Wang yu&Yang Xiaowei.(2016).Application of Decision Tree for MRI Images of Premature Brain Injury Classification.2016 11TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE),,
MLA：
Wang yu,et al."Application of Decision Tree for MRI Images of Premature Brain Injury Classification".2016 11TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE) .(2016):792-795
