Automatic Detection of COVID-19 from Chest X-ray Images Using Deep Learning Model
This work addresses the urgent need for automated COVID-19 diagnosis in healthcare systems, but it appears incremental as it applies existing deep learning methods to a new medical imaging task.
The authors tackled the problem of COVID-19 detection from chest X-ray images using deep learning models to address the scarcity of conventional test kits, achieving satisfactory and promising results compared to previous methods.
The infectious disease caused by novel corona virus (2019-nCoV) has been widely spreading since last year and has shaken the entire world. It has caused an unprecedented effect on daily life, global economy and public health. Hence this disease detection has life-saving importance for both patients as well as doctors. Due to limited test kits, it is also a daunting task to test every patient with severe respiratory problems using conventional techniques (RT-PCR). Thus implementing an automatic diagnosis system is urgently required to overcome the scarcity problem of Covid-19 test kits at hospital, health care systems. The diagnostic approach is mainly classified into two categories-laboratory based and Chest radiography approach. In this paper, a novel approach for computerized corona virus (2019-nCoV) detection from lung x-ray images is presented. Here, we propose models using deep learning to show the effectiveness of diagnostic systems. In the experimental result, we evaluate proposed models on publicly available data-set which exhibit satisfactory performance and promising results compared with other previous existing methods.