Automatic detection of major lung diseases using Chest Radiographs and classification by feed-forward artificial neural network

Shubhangi Khobragade, A. Tiwari, C. Patil, Vikram D. Narke
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引用次数: 82

Abstract

Chest Radiograph is the preliminary requirement for the identification of lung diseases. Tuberculosis; pneumonia and lung cancer these lung diseases are major health threat. According to recent survey; which was given by WHO; rate of people dying due to late diagnosis of lung diseases is in millions. Early diagnosis of these diseases can curb mortality rate. This paper proposes lung segmentation; lung feature extraction and it's classification using artificial neural network technique for the detection of lung diseases such as TB; lung cancer and pneumonia. We have used the simple image processing techniques like intensity based method and discontinuity based method to detect lung boundaries. Statistical and geometrical features are extracted. Image classification using feed forward and back propagation neural network to detect major lung diseases.
基于胸片的重大肺部疾病自动检测及前馈人工神经网络分类
胸片检查是鉴别肺部疾病的初步要求。肺结核;肺炎和肺癌这些肺部疾病是主要的健康威胁。根据最近的调查;由世卫组织提供;由于肺部疾病的晚期诊断而死亡的人数以百万计。这些疾病的早期诊断可以控制死亡率。本文提出了肺分割;基于人工神经网络技术的肺部特征提取及分类在肺结核等肺部疾病检测中的应用肺癌和肺炎。我们使用简单的图像处理技术,如基于强度的方法和基于不连续的方法来检测肺边界。提取统计和几何特征。基于前馈和反向传播神经网络的图像分类检测肺部重大疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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