Background Automated segmentation of anatomical structures is a crucial step in image
analysis. For lung segmentation in computed tomography, a variety of approaches exists …

Computed tomography (CT) is the modality of choice for imaging the lungs in vivo. Sub-
millimeter isotropic images of the lungs can be obtained within seconds, allowing the …

Objectives: Automated computational segmentation of the lung and its lobes and findings in
X-Ray based computed tomography (CT) images is a challenging problem with important …

To accurately segment pathological and healthy lungs for reliable computer-aided disease
diagnostics, a stack of chest CT scans is modeled as a sample of a spatially inhomogeneous …

Computer-aided detection and diagnosis (CAD) has been widely investigated to improve
radiologists׳ diagnostic accuracy in detecting and characterizing lung disease, as well as to …

Purpose: Accurate segmentation of lungs with severe interstitial lung disease (ILD) in
thoracic computed tomography (CT) is an important and difficult task in the development of …

Simple Summary Pulmonary nodules are considered a sign of bronchogenic carcinoma,
detecting them early will reduce their progression and can save lives. Lung cancer is the …

Purpose To conduct a meta-analysis to determine specific computed tomography (CT)
patterns and clinical features that discriminate between nonspecific interstitial pneumonia …

Respiratory tract infections are a leading cause of death and disability worldwide. Although
radiology serves as a primary diagnostic method for assessing respiratory tract infections …

A new segmentation technique is introduced for delineating the lung region in 3D computed
tomography (CT) images. To accurately model the distribution of Hounsfield scale values …