Artificial intelligence-based fully automated per lobe segmentation and emphysema-quantification based on chest computed tomography compared with global …

AM Fischer, A Varga-Szemes, SS Martin… - Journal of Thoracic …, 2020 - journals.lww.com
Objectives: The objective of this study was to evaluate an artificial intelligence (AI)-based
prototype algorithm for the fully automated per lobe segmentation and emphysema …

COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images

L Zhang, B Jiang, HJ Wisselink… - The British Journal of …, 2022 - academic.oup.com
Objective Chest CT can display the main pathogenic factors of chronic obstructive
pulmonary disease (COPD), emphysema and airway wall remodeling. This study aims to …

[HTML][HTML] Automated lung segmentation on chest computed tomography images with extensive lung parenchymal abnormalities using a deep neural network

SJ Yoo, SH Yoon, JH Lee, KH Kim, HI Choi… - Korean journal of …, 2021 - ncbi.nlm.nih.gov
Objective We aimed to develop a deep neural network for segmenting lung parenchyma
with extensive pathological conditions on non-contrast chest computed tomography (CT) …

A lung dense deep convolution neural network for robust lung parenchyma segmentation

Y Chen, Y Wang, F Hu, D Wang - IEEE Access, 2020 - ieeexplore.ieee.org
Lung parenchyma segmentation is the prerequisite for an automatic diagnosis system to
analyze lung CT (computed tomography) images. However, traditional lung segmentation …

Automated CT staging of chronic obstructive pulmonary disease severity for predicting disease progression and mortality with a deep learning convolutional neural …

KA Hasenstab, N Yuan, T Retson… - Radiology …, 2021 - pubs.rsna.org
Purpose To develop a deep learning–based algorithm to stage the severity of chronic
obstructive pulmonary disease (COPD) through quantification of emphysema and air …

Automated segmentation of pulmonary lobes using coordination-guided deep neural networks

W Wang, J Chen, J Zhao, Y Chi, X Xie… - 2019 IEEE 16th …, 2019 - ieeexplore.ieee.org
The identification of pulmonary lobes is of great importance in disease diagnosis and
treatment. A few lung diseases have regional disorders at lobar level. Thus, an accurate …

Automatic lung segmentation in low-dose chest CT scans using convolutional deep and wide network (CDWN)

S Akila Agnes, J Anitha, J Dinesh Peter - Neural Computing and …, 2020 - Springer
Computed tomography (CT) imaging is the preferred imaging modality for diagnosing lung-
related complaints. Automatic lung segmentation is the most common prerequisite to …

Fully automated lung lobe segmentation in volumetric chest CT with 3D U-Net: validation with intra-and extra-datasets

J Park, J Yun, N Kim, B Park, Y Cho, HJ Park… - Journal of digital …, 2020 - Springer
Lung lobe segmentation in chest CT has been used for the analysis of lung functions and
surgical planning. However, accurate lobe segmentation is difficult as 80% of patients have …

Lung segmentation-based pulmonary disease classification using deep neural networks

SZY Zaidi, MU Akram, A Jameel, NS Alghamdi - IEEE Access, 2021 - ieeexplore.ieee.org
Interpreting chest x-ray (CXR) to find anomalies in the thoracic region is a tedious job and
can consume an ample amount of radiologist's time when there are thousands of them to …

Comparison of artificial intelligence–based fully automatic chest CT emphysema quantification to pulmonary function testing

AM Fischer, A Varga-Szemes… - American Journal of …, 2020 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this study was to evaluate an artificial intelligence (AI)-based
prototype algorithm for fully automated quantification of emphysema on chest CT compared …