Concept

Pneumopathie interstitielle

Publications associées (49)

Quantitative T2 Mapping of Acute Pancreatitis

Background: Quantification of the T2 signal by means of T2 mapping in acute pancreatitis (AP) has the potential to quantify the parenchymal edema. Quantitative T2 mapping may overcome the limitations of previously reported scoring systems for reliable asse ...

Hoboken2024

Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study

Mary-Anne Hartley

BackgroundInterstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognosis. Prom ...

BMC2023

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening

Jiancheng Yang, Zhiye Wang, Jun Lu, Zhigang Li, Lin Qi, Ming Li, Bo Du, Yuxuan Sun, Ziyi Liu

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 can eff ...

London2023

Multi-site, Multi-domain Airway Tree Modeling

Jiancheng Yang, Yi Wu, Ying Zhu, Boyu Zhang

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolut ...

Amsterdam2023

Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset

Jiancheng Yang

Accurate segmentation of pulmonary airways and vessels is crucial for the diagnosis and treatment of pulmonary diseases. However, current deep learning approaches suffer from disconnectivity issues that hinder their clinical usefulness. To address this cha ...

Cham2023

Impact of COVID-19 on long-term lung function in lung transplant recipients: A single-center retrospective cohort study

Nahal Mansouri

Available data are limited concerning long-term lung function (LF) evolution after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in lung transplant (LT) recipients. The aim of this study is to determine the effect of first SARS-CoV ...

WILEY2023

Efficient Lung Nodule Detection via 3D Deep Learning with Shifted Convolutions

Jiancheng Yang, Bo Du, Kang Yuan

The high computational costs of deep convolutional neural networks hinder their deployment in real-world applications, including pulmonary nodule detection from CT scans where large 3D image sizes amplify the issue. This paper presents a novel 3D method to ...

IEEE2023

Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation

Qian Wang, Tobias Kober, Tom Hilbert, Yao Zhang, Yubo Zhao

Objective To investigate the utility of an automatic deep learning (DL) method for segmentation of T2 maps in patients with idiopathic inflammatory myopathy (IIM) against healthy controls, and also the association of quantitative T2 values in patients with ...

SPRINGER2022

Novel trehalose-based excipients for stabilizing nebulized anti-SARS-CoV-2 antibody

Sandrine Gerber, François Rémi Pierre Noverraz, Solène Marcelle Françoise Marie Passemard

COVID-19 is caused by the infection of the lungs by SARS-CoV-2. Monoclonal antibodies, such as sotrovimab, showed great efficiency in neutralizing the virus before its internalization by lung epithelial cells. However, parenteral routes are still the prefe ...

2022

Improving the efficiency of identifying malignant pulmonary nodules before surgery via a combination of artificial intelligence CT image recognition and serum autoantibodies

Jiancheng Yang, Yi Ding, Zhen Gao

ObjectiveTo construct a new pulmonary nodule diagnostic model with high diagnostic efficiency, non-invasive and simple to measure. MethodsThis study included 424 patients with radioactive pulmonary nodules who underwent preoperative 7-autoantibody (7-AAB) ...

SPRINGER2022

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