计算机应用与软件Issue(2)：171-173,177,4.DOI:10.3969/j.issn.1000-386x.2015.02.043
灰度共生矩阵在尘肺阴影密集度判读中的应用
APPLICATION OF GLCM IN INTERPRETATION OF PNEUMOCONIOSIS SHADOWGRAPH INTENSITY
摘要
Abstract
In the process of realising automatic interpretation of pneumoconiosis in different stages,we propose the pneumoconiosis intensity interpretation method,which is based on the combination of GLCM (gray level co-occurrence matrix)and BP neural network and aiming at the problem that the impact of pneumoconiosis lesions diversity on X-RAY DR chest radiograph leads to the impossibility of directly obtaining the shadowgraph intensity by measuring the size of shadow area.Simulation experiments of pneumoconiosis samples in different stages are carried out using Matlab,and the results show that the four eigenvalues generated by GLCMcan effectively describe the texture fea-tures of the chest radiograph of pneumoconiosis in different stages.Moreover,it is able to realise the effective interpretation of shadowgraph intensity of pneumoconiosis through BP neural network classification.关键词
尘肺病/肺野纹理/灰度共生矩阵/BP神经网络/Bootstrap法Key words
Pneumoconiosis/Lung field texture/Gray level co-occurrence matrix/BP neural network/Bootstrap method分类
信息技术与安全科学引用本文复制引用
罗海峰,翟荣存..灰度共生矩阵在尘肺阴影密集度判读中的应用[J].计算机应用与软件,2015,(2):171-173,177,4.基金项目
安徽省教育厅自然科学基金重点项目 （）
