%0 Journal Article
%T Research on Data Processing Approaches to Auto-fluorescence Spectrogram for Colorectal Carcinoma<br>大肠癌自体荧光光谱信号处理方法研究*
%A FAN Xiao-ping
%A LIU Xiao
%A LIAO Zhi-fang
%A LI Yi-fan
%A ZHANG Yang-de
%A <br>樊晓平
%A 刘皛
%A 廖志芳
%A 李异凡
%A 张阳德
%J 计算机应用研究
%D 2007
%I 
%X Several signal analysis methods were described and compared which are applied to deal with the spectrum data. And then, a new method was presented to carry out the data processing based on decision trees. By training and classifying the data of normal tissues and cancerous ones, this new method was proved to be useful in diagnosing the colorectal carcinoma at its early stage effectively.
%K colorectal carcinoma
%K auto-fluorescence spectrogram
%K signal analysis
%K decision trees<br>大肠癌
%K 自体荧光光谱
%K 信号分析
%K 决策树
%K 大肠癌
%K 荧光光谱
%K 信号处理方法
%K 研究
%K Colorectal
%K Carcinoma
%K Spectrogram
%K Data
%K Processing
%K 诊断和治疗
%K 大肠早癌
%K 指导
%K 分类效果
%K 处理结果
%K 训练
%K 样本数据
%K 病症
%K 算法
%K 决策树
%K 方差
%K 比较
%K 正常组织
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C793235A4E87B8F6E8B44416C57065C4&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=B31275AF3241DB2D&sid=D6354F61445E9456&eid=E1D946F217E3B046&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=1&reference_num=6