An Add-on CNN based Model for the Detection of Tuberculosis using Chest X-ray Images

IF 0.7 Q3 COMPUTER SCIENCE, THEORY & METHODS
Roopa N K, M. S
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引用次数: 0

Abstract

—Machine Learning has been potentially contributing towards smart diagnosis in the medical domain for more than a decade with a target towards achieving higher accuracy in detection and classification. However, from the perspective of medical image processing, the contribution of machine learning towards segmentation is not been much to find in recent times. The proposed study considers a use case of Tuberculosis detection and classification from chest x-rays where a unique machine learning approach of Convolution Neural Network is adopted for segmentation of lung images from CXR. A computational framework is developed that performs segmentation, feature extraction, detection, and classification. The proposed system's study outcome is analyzed with and without segmentation over existing machine learning models to exhibit 99.85% accuracy, which is the highest score to date in contrast to existing approaches found in the literature. The study outcome based on the comparative analysis exhibits the effectiveness of the proposed system.
基于CNN的胸部x线图像肺结核检测附加模型
十多年来,机器学习一直在为医疗领域的智能诊断做出潜在贡献,其目标是实现更高的检测和分类准确性。然而,从医学图像处理的角度来看,近年来机器学习在分割方面的贡献并不多见。提出的研究考虑了从胸部x射线中检测和分类结核病的用例,其中采用独特的卷积神经网络机器学习方法对来自CXR的肺部图像进行分割。开发了一个执行分割、特征提取、检测和分类的计算框架。该系统的研究结果在现有机器学习模型上进行了分割和不分割的分析,显示出99.85%的准确率,这是迄今为止与文献中发现的现有方法相比的最高分。通过对比分析得出的研究结果表明了该系统的有效性。
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来源期刊
CiteScore
2.30
自引率
22.20%
发文量
519
期刊介绍: IJACSA is a scholarly computer science journal representing the best in research. Its mission is to provide an outlet for quality research to be publicised and published to a global audience. The journal aims to publish papers selected through rigorous double-blind peer review to ensure originality, timeliness, relevance, and readability. In sync with the Journal''s vision "to be a respected publication that publishes peer reviewed research articles, as well as review and survey papers contributed by International community of Authors", we have drawn reviewers and editors from Institutions and Universities across the globe. A double blind peer review process is conducted to ensure that we retain high standards. At IJACSA, we stand strong because we know that global challenges make way for new innovations, new ways and new talent. International Journal of Advanced Computer Science and Applications publishes carefully refereed research, review and survey papers which offer a significant contribution to the computer science literature, and which are of interest to a wide audience. Coverage extends to all main-stream branches of computer science and related applications
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