Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs
المؤلفون المشاركون
Zhu, Zhaohui
Wu, Yifan
Han, Xin
Xie, Yilin
Cui, Lei
Chen, Zhongyuanlong
Wu, Zhuoyue
Wang, Hongyu
Feng, Jun
المصدر
Journal of Healthcare Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-24
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
The early screening and diagnosis of tuberculosis plays an important role in the control and treatment of tuberculosis infections.
In this paper, an integrated computer-aided system based on deep learning is proposed for the detection of multiple categories of tuberculosis lesions in chest radiographs.
In this system, the fully convolutional neural network method is used to segment the lung area from the entire chest radiograph for pulmonary tuberculosis detection.
Different from the previous analysis of the whole chest radiograph, we focus on the specific tuberculosis lesion areas for the analysis and propose the first multicategory tuberculosis lesion detection method.
In it, a learning scalable pyramid structure is introduced into the Faster Region-based Convolutional Network (Faster RCNN), which effectively improves the detection of small-area lesions, mines indistinguishable samples during the training process, and uses reinforcement learning to reduce the detection of false-positive lesions.
To compare our method with the current tuberculosis detection system, we propose a classification rule for whole chest X-rays using a multicategory tuberculosis lesion detection model and achieve good performance on two public datasets (Montgomery: AUC = 0.977 and accuracy = 0.926; Shenzhen: AUC = 0.941 and accuracy = 0.902).
Our proposed computer-aided system is superior to current systems that can be used to assist radiologists in diagnoses and public health providers in screening for tuberculosis in areas where tuberculosis is endemic.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Xie, Yilin& Wu, Zhuoyue& Han, Xin& Wang, Hongyu& Wu, Yifan& Cui, Lei…[et al.]. 2020. Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1186714
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Xie, Yilin…[et al.]. Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs. Journal of Healthcare Engineering No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1186714
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Xie, Yilin& Wu, Zhuoyue& Han, Xin& Wang, Hongyu& Wu, Yifan& Cui, Lei…[et al.]. Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1186714
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1186714
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر