昆明医学院学报2012，Vol.33Issue(1)：29-32,4.
基于形态学特征提取的人工神经网络在口腔鳞状细胞癌诊断中的应用
Application of Artificial Neural Network based on Morphometric Feature Extraction in Diagnosis of Oral Squamous Cell Carcinoma
摘要
Abstract
Objective To find a feasible and convenient way to help pathologist to analyze cell features of oral squamous cell carcinoma, an artificial neural network (radial basis function) has been applied based on the morphometric image processing. Methods Some images of histopahological sections of patients suffering from oral squamous cell carcinoma and non- carcinoma epithelium were selected to train a RBF network. The network was based on a morphometric method to extract a feature vector. Another 67 images of sections including oral squamous cell carcinoma and non- carcinoma were tested by the trained network to evaluate the performance of RBF network. Result Through the analysis of the output of trained RBF network classification, different sensitivity and specificity of diagnosis was achieved by choosing different threshold value correspongingly. Conclusion RBF network is a feasible auxiliary tool in the diagnosis of oral squamous cell carcinoma, even though it can not be a precise diagnosis standard.关键词
口腔鳞状细胞癌/神经网络(计算机)/图像处理Key words
Oral squamous cell carcinoma/ Neural network/ Image processing分类
医药卫生引用本文复制引用
马开宇,马开阳,黎明,代晓明,李逸松..基于形态学特征提取的人工神经网络在口腔鳞状细胞癌诊断中的应用[J].昆明医学院学报,2012,33(1):29-32,4.基金项目
云南省科技厅- 昆明医学院联合专项基金资助项目(2010CD216) （2010CD216）
