We propose a deep learning system to automatically detect four explainable emphysema signs on frontal and lateral chest radiographs. Frontal and lateral chest radiographs from 3000 studies were retrospectively collected. Two radiologists annotated th...
PURPOSE: We aimed to identify clinically relevant deep learning algorithms for emphysema quantification using low-dose chest computed tomography (LDCT) through an invitation-based competition.
Mathematical biosciences and engineering : MBE
May 7, 2022
Cardiothoracic diseases are a serious threat to human health and chest X-ray image is a great reference in diagnosis and treatment. At present, it has been a research hot-spot how to recognize chest X-ray image automatically and exactly by the comput...
Background and Objectives: Although reducing the radiation dose level is important during diagnostic computed tomography (CT) applications, effective image quality enhancement strategies are crucial to compensate for the degradation that is caused by...
In addition to lung cancer, other thoracic abnormalities, such as emphysema, can be visualized within low-dose CT scans that were initially obtained in cancer screening programs, and thus, opportunistic evaluation of these diseases may be highly valu...
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
Aug 16, 2023
INTRODUCTION: With global adoption of computed tomography (CT) lung cancer screening, there is increasing interest to use artificial intelligence (AI) deep learning methods to improve the clinical management process. To enable AI research using an op...
American journal of respiratory and critical care medicine
Sep 15, 2023
Although studies have evaluated emphysema and fibrotic interstitial lung abnormality individually, less is known about their combined progression. To define clinically meaningful progression of fibrotic interstitial lung abnormality in smokers with...
OBJECTIVES: Parametric response mapping (PRM) enables the evaluation of small airway disease (SAD) at the voxel level, but requires both inspiratory and expiratory chest CT scans. We hypothesize that deep learning PRM from inspiratory chest CT scans ...
OBJECTIVES: The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep learning-based kernel adaptation on long-term mortality.