As the most common examination tool in medical practice, chest radiography has important
clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease …

Deep learning (DL) has shown rapid advancement and considerable promise when applied
to the automatic detection of diseases using CXRs. This is important given the widespread …

Abstract Coronavirus (COVID-19) has adversely harmed the healthcare system and
economy throughout the world. COVID-19 has similar symptoms as other chest disorders …

Pneumonia is among the most prevalent diseases, and due to lack of experts it is difficult to
detect. This paper focuses on surveying and comparing the detection of lung disease using …

The human respiratory network is a vital system that provides oxygen supply and
nourishment to the whole body. Pulmonary diseases can cause severe respiratory …

COVID-19, which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-
CoV-2), is one of the worst pandemics in recent history. The identification of patients …

The early screening and diagnosis of tuberculosis plays an important role in the control and
treatment of tuberculosis infections. In this paper, an integrated computer‐aided system …

Chest radiography is the standard and most affordable way to diagnose, analyze, and
examine different thoracic and chest diseases. Typically, the radiograph is examined by an …

We propose a deep learning framework to improve segmentation accuracy of the lung
region in Chest X-Ray (CXR) images. The proposed methodology implements a “divide and …

Objectives To investigate the optimal input matrix size for deep learning-based computer-
aided detection (CAD) of nodules and masses on chest radiographs. Methods We …