Automated computer-aided diagnosis of COVID-19 and pneumonia based on chest X-ray images using deep learning: Classification and segmentation

Diagnosis of COVID-19 using artificial intelligence has been the focus of multiple researchers and institutions to alleviate the work pressure of frontline radiologists and contribute to the control of the epidemic through early diagnosis of the virus, isolation prevention and effective treatment of the disease in patients. In this chapter, three fields are addressed for the application of artificial intelligence in the diagnosis of pulmonary pathologies. This chapter addresses several fields for the application of artificial intelligence in the diagnosis of pulmonary pathologies. It proposes an efficient, low-cost and versatile deep learning based approach for automated computer-assisted diagnosis of COVID-19 and pneumonia using segmentation and classification techniques on chest X-ray images. Computer-aided detection and diagnosis of pulmonary pathologies based on X-ray images is a field of computer science research that was developed in the 1960s and has been under development in recent decades. Medical imaging plays a major role in disease diagnosis in multiple medical fields, ranging from lung cancer screening to prostate cancer staging. Clinical care has broadened its interest in the application of Machine Learning techniques for the extraction of features that allow providing critical information about the internal state of the patient through computed tomography, magnetic resonance imaging, digital mammography, among many others imaging in remote modalities.