The segmentation of lungs from medical images is a critical step in the diagnosis and
treatment of lung diseases. Deep learning techniques have shown great promise in …

Medical image segmentation is a crucial step in developing computer-Aided Diagnosis
(CAD), which supports the physician to adopt a suitable procedure about the clinical case …

Medical imaging, such as chest X-rays, gives an acceptable image of lung functions.
Manipulating these images by a radiologist is difficult, thus delaying the diagnosis …

Medical image segmentation is a crucial stage in computer vision and image processing to
help the later-stage diagnosis process become more accurate. Because medical image …

Deep neural networks have entirely dominated the machine vision space in the past few
years due to their astonishing human comparable performance. This paper applies power of …

Lung cancer is, by far, the leading cause of cancer death in the world. Tools for automated
medical imaging analysis development of a Computer-Aided Diagnosis method comprises …

Computed tomography (CT) imaging is the preferred imaging modality for diagnosing lung-
related complaints. Automatic lung segmentation is the most common prerequisite to …

A chest radiograph, commonly called chest x-ray (CxR), plays a vital role in the diagnosis of
various lung diseases. Automated segmentation of the lungs is an important step to design a …

COVID-19 patients require effective diagnostic methods, which are currently in short supply.
In this study, we explained how to accurately identify the lung regions on the X-ray scans of …

Abstract Background and Objective Chest X-ray (CXR) is one of the most used imaging
techniques for detection and diagnosis of pulmonary diseases. A critical component in any …