查询结果:   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,2015,32(2):171 - 173,177.
中文标题
灰度共生矩阵在尘肺阴影密集度判读中的应用
发表栏目
人工智能与识别
摘要点击数
896
英文标题
APPLICATION OF GLCM IN INTERPRETATION OF PNEUMOCONIOSIS SHADOWGRAPH INTENSITY
作 者
罗海峰 翟荣存 Luo Haifeng Zhai Rongcun
作者单位
中国科学技术大学计算机科学与技术学院 安徽 合肥 230026 安徽工业职业技术学院信息工程系 安徽 铜陵 244000 铜陵有色职工总医院影像中心 安徽 铜陵 244000   
英文单位
School of Computer Science and Technology,University of Science and Technology of China,Hefei 230026, Anhui, China Department of Information Engineering,Anhui Industrial Vocational and Technical College,Tongling 244000, Anhui, China Imaging Center of Tongling Non-ferrous Worker’s Hospital,Tongling 244000, Anhui, China   
关键词
尘肺病 肺野纹理 灰度共生矩阵 BP神经网络 Bootstrap法
Keywords
Pneumoconiosis Lung field texture Gray level co-occurrence matrix BP neural network Bootstrap method
基金项目
安徽省教育厅自然科学基金重点项目(KJ2014A032)
作者资料
罗海峰,高工,主研领域:模式识别与图像处理。翟荣存,学士。 。
文章摘要
在实现尘肺病的自动分期判读过程中,针对X射线DR胸片受到尘肺病变多样性的影响导致无法直接通过测量阴影大小来准确获取阴影密集度的问题,提出基于灰度共生矩阵与BP神经网络相结合的尘肺密集度判读方法。通过Matlab对不同期别的尘肺样本进行仿真实验,结果表明由灰度共生矩阵产生的四个特征值能对不同期别尘肺胸片的纹理特征进行有效描述,并通过BP神经网络分类可实现对尘肺阴影密集度的有效判读。
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 GLCM can effectively describe the texture features 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.
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