Detection Covid-19 based on chest X-ray images using convolution neural networks

المؤلفون المشاركون

Ali, Akbas Izz al-Din
Zabin, Sufyan Uthman

المصدر

Iraqi Journal of Computer, Communications and Control Engineering

العدد

المجلد 22، العدد 1 (31 مارس/آذار 2022)، ص ص. 34-42، 9ص.

الناشر

الجامعة التكنولوجية

تاريخ النشر

2022-03-31

دولة النشر

العراق

عدد الصفحات

9

التخصصات الرئيسية

الطب البشري

الملخص EN

Covid-19 is a deadly virus that has spread worldwide, causing millions of deaths.

Chest X-ray is one of the most common methods of diagnosing the infection of Covid -19.

therefore, this paper has presented an efficient method to detect Covid-19 through X-rays of the chest area through a Neural convolution network (CNN).

the proposed system has used a convolution neural network to classify the extracted features.

Since CNN needs a set of data defined for training and testing, the proposed method used a public dataset of 350 pneumonia x-ray images, 300 viral images, and 350 normal images for evaluation.

besides, the proposed work achieved a satisfactory accuracy of 95% based on the X-ray image.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Zabin, Sufyan Uthman& Ali, Akbas Izz al-Din. 2022. Detection Covid-19 based on chest X-ray images using convolution neural networks. Iraqi Journal of Computer, Communications and Control Engineering،Vol. 22, no. 1, pp.34-42.
https://search.emarefa.net/detail/BIM-1493012

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Zabin, Sufyan Uthman& Ali, Akbas Izz al-Din. Detection Covid-19 based on chest X-ray images using convolution neural networks. Iraqi Journal of Computer, Communications and Control Engineering Vol. 22, no. 1 (Mar. 2022), pp.34-42.
https://search.emarefa.net/detail/BIM-1493012

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Zabin, Sufyan Uthman& Ali, Akbas Izz al-Din. Detection Covid-19 based on chest X-ray images using convolution neural networks. Iraqi Journal of Computer, Communications and Control Engineering. 2022. Vol. 22, no. 1, pp.34-42.
https://search.emarefa.net/detail/BIM-1493012

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references : p. 41-42

رقم السجل

BIM-1493012