Optimizing Convolutional Neural Networks for Chronic Obstructive Pulmonary Disease Detection in Clinical Computed Tomography Imaging [PDF]
Comput Biol Med 185, 109533 (2025), 2023 We aim to optimize the binary detection of Chronic Obstructive Pulmonary Disease (COPD) based on emphysema presence in the lung with convolutional neural networks (CNN) by exploring manually adjusted versus automated window-setting optimization (WSO) on computed tomography (CT) images.
arxiv +1 more source
Emphysema Subtyping on Thoracic Computed Tomography Scans using Deep Neural Networks [PDF]
Sci Rep. 2023 Aug 29;13(1):14147, 2023 Accurate identification of emphysema subtypes and severity is crucial for effective management of COPD and the study of disease heterogeneity. Manual analysis of emphysema subtypes and severity is laborious and subjective. To address this challenge, we present a deep learning-based approach for automating the Fleischner Society's visual score system ...
arxiv +1 more source
Elastocapillary network model of inhalation [PDF]
Physical Review Research, 2, 043382 (2020), 2020 The seemingly simple process of inhalation relies on a complex interplay between muscular contraction in the thorax, elasto-capillary interactions in individual lung branches, propagation of air between different connected branches, and overall air flow into the lungs.
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Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images [PDF]
, 2017 A method for automatically quantifying emphysema regions using High-Resolution Computed Tomography (HRCT) scans of patients with chronic obstructive pulmonary disease (COPD) that does not require manually annotated scans for training is presented. HRCT scans of controls and of COPD patients with diverse disease severity are acquired at two different ...
arxiv +1 more source
Deep learning automated quantification of lung disease in pulmonary hypertension on CT pulmonary angiography: A preliminary clinical study with external validation [PDF]
arXiv, 2023 Purpose: Lung disease assessment in precapillary pulmonary hypertension (PH) is essential for appropriate patient management. This study aims to develop an artificial intelligence (AI) deep learning model for lung texture classification in CT Pulmonary Angiography (CTPA), and evaluate its correlation with clinical assessment methods.
arxiv
Novel Subtypes of Pulmonary Emphysema Based on Spatially-Informed Lung Texture Learning [PDF]
arXiv, 2020 Pulmonary emphysema overlaps considerably with chronic obstructive pulmonary disease (COPD), and is traditionally subcategorized into three subtypes previously identified on autopsy. Unsupervised learning of emphysema subtypes on computed tomography (CT) opens the way to new definitions of emphysema subtypes and eliminates the need of thorough manual ...
arxiv
Entropy Production and the Pressure-Volume Curve of the Lung [PDF]
, 2015 We investigate analytically the production of entropy during a breathing cycle in healthy and diseased lungs. First, we calculate entropy production in healthy lungs by applying the laws of thermodynamics to the well-known transpulmonary pressure-volume ($P-V$) curves of the lung under the assumption that lung tissue behaves as an entropy spring-like ...
arxiv +1 more source
Initial non-invasive in vivo sensing of the lung using time domain diffuse optics [PDF]
arXiv, 2022 Non-invasive in vivo sensing of the lung with light would help diagnose and monitor pulmonary disorders (caused by e.g. COVID-19, emphysema, immature lung tissue in infants). We investigated the possibility to probe the lung with time domain diffuse optics, taking advantage of the increased depth (few cm) reached by photons detected after a long (few ...
arxiv
Can Deep Learning Reliably Recognize Abnormality Patterns on Chest X-rays? A Multi-Reader Study Examining One Month of AI Implementation in Everyday Radiology Clinical Practice [PDF]
arXiv, 2023 In this study, we developed a deep-learning-based automatic detection algorithm (DLAD, Carebot AI CXR) to detect and localize seven specific radiological findings (atelectasis (ATE), consolidation (CON), pleural effusion (EFF), pulmonary lesion (LES), subcutaneous emphysema (SCE), cardiomegaly (CMG), pneumothorax (PNO)) on chest X-rays (CXR).
arxiv
COPD Classification in CT Images Using a 3D Convolutional Neural Network [PDF]
arXiv, 2020 Chronic obstructive pulmonary disease (COPD) is a lung disease that is not fully reversible and one of the leading causes of morbidity and mortality in the world. Early detection and diagnosis of COPD can increase the survival rate and reduce the risk of COPD progression in patients.
arxiv