Challenges for the effective management of interstitial lung diseases (ILDs) include
difficulties with the early detection of disease, accurate prognostication with baseline data …

Chest X-ray radiography and computed tomography, the two mainstay modalities in thoracic
radiology, are under active investigation with deep learning technology, which has shown …

The purpose of this statement is to describe and define the phenotypic abnormalities that
can be identified on visual and quantitative evaluation of computed tomographic (CT) …

Multidetector row computed tomography (MDCT) is increasingly taking a central role in
identifying subphenotypes within chronic obstructive pulmonary disease (COPD), asthma …

Purpose To develop a deep learning–based algorithm to stage the severity of chronic
obstructive pulmonary disease (COPD) through quantification of emphysema and air …

Rationale and Objectives The longitudinal relationship between regional air trapping and
emphysema remains unexplored. We have sought to demonstrate the utility of parametric …

Background Visual assessment remains the standard for evaluating emphysema at CT;
however, it is time consuming, is subjective, requires training, and is affected by variability …

Background Experience with functional CT in the lungs without additional equipment in
clinical routine is limited. Purpose To report initial experience and evaluate the robustness of …

Background The mechanisms underlying airflow obstruction in COPD cannot be
distinguished by standard spirometry. We ascertain whether mathematical modeling of …

The classification and segmentation of pathologies through intelligent systems is a
significant challenge for medical image analysis and computer vision systems. Diseases …