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All Journal Proceeding of International Conference Health, Science And Technology (ICOHETECH)
Indra Agung Yudistira
Universitas Duta Bangsa Surakarta
Computer Science & IT Decision Sciences, Operations Research & Management Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology

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Detection of Covid-19 on X-Ray Images Using a Deep Learning Convolution Neural Network Sri Widodo; Anik Sulistiyanti; Indra Agung Yudistira; Maryatun
Proceeding of International Conference on Science, Health, And Technology 2021: Proceeding of the 2nd International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1887.08 KB) | DOI: 10.47701/icohetech.v1i1.1136

Abstract

Pneumonia Coronavirus Disease 2019 (COVID-19) is an inflammation of the lung parenchyma caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Supporting examinations carried out to establish a diagnosis of Covid-19 is through radiological examinations, one of which is a X-Ray The current method used to diagnose COVID-19 from X-Ray images is by studying the 2-D X-Ray image data set using the naked eye, then interpreting the data one by one. This procedure is ineffective. Proposed research aims to develop a Covid-19 detection application on localized X-Ray images using a Deep Learning Convolution Neural Network. This research includes four main points. The first is taking a X-Ray image from the internet. The second is X-Ray image preprocessing. The third is the determination of Region of Interest (ROI) from X-Ray imagery containing Covid-19 and normal X-Ray. The fourth is to detect COVID-19 automatically by classifying image suspected of being COVID-19 on X-Ray using the Deep Learning Convolution Neural Network method. The accuracy obtained is an accuracy of 95%.
Co-Authors Anik Sulistiyanti Maryatun Sri Widodo