Detection of Covid-19 on X-Ray Images Using a Deep Learning Convolution Neural Network

Sri Widodo (Universitas Duta Bangsa Surakarta)
Anik Sulistiyanti (Universitas Duta Bangsa Surakarta)
Indra Agung Yudistira (Universitas Duta Bangsa Surakarta)
Maryatun (Universitas Aisyiyah Surakarta)

Proceeding of International Conference Health, Science And Technology (ICOHETECH)
2021: Proceeding of the 2nd International Conference Health, Science And Technology (ICOHETECH)

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%.