Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans
Purpose The proposed work aims to develop an algorithm to precisely segment the lung
parenchyma in thoracic CT scans. To achieve this goal, the proposed technique utilized a …
parenchyma in thoracic CT scans. To achieve this goal, the proposed technique utilized a …
Three-stage segmentation of lung region from CT images using deep neural networks
M Osadebey, HK Andersen, D Waaler, K Fossaa… - BMC Medical …, 2021 - Springer
Background Lung region segmentation is an important stage of automated image-based
approaches for the diagnosis of respiratory diseases. Manual methods executed by experts …
approaches for the diagnosis of respiratory diseases. Manual methods executed by experts …
Computer-Aided Lung Parenchyma Segmentation Using Supervised Learning
GN Balaji, P Subramanian - … Science and Engineering: Proceedings of the …, 2019 - Springer
Advances in the fields of image processing and information technology have led to the use
of computers for the diagnosis of diseases. This has led to the emergence of Computer …
of computers for the diagnosis of diseases. This has led to the emergence of Computer …
Fully automated lung lobe segmentation in volumetric chest CT with 3D U-Net: validation with intra-and extra-datasets
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 …
surgical planning. However, accurate lobe segmentation is difficult as 80% of patients have …
Deep Learning–based Automatic Lung Segmentation on Multiresolution CT Scans from Healthy and Fibrotic Lungs in Mice
F Sforazzini, P Salome, M Moustafa, C Zhou… - Radiology: Artificial …, 2022 - pubs.rsna.org
Purpose To develop a model to accurately segment mouse lungs with varying levels of
fibrosis and investigate its applicability to mouse images with different resolutions. Materials …
fibrosis and investigate its applicability to mouse images with different resolutions. Materials …
An effective approach for CT lung segmentation using mask region-based convolutional neural networks
Q Hu, LFF Souza, GB Holanda, SSA Alves… - Artificial intelligence in …, 2020 - Elsevier
Computer vision systems have numerous tools to assist in various medical fields, notably in
image diagnosis. Computed tomography (CT) is the principal imaging method used to assist …
image diagnosis. Computed tomography (CT) is the principal imaging method used to assist …
RPLS-Net: pulmonary lobe segmentation based on 3D fully convolutional networks and multi-task learning
J Liu, C Wang, J Guo, J Shao, X Xu, X Liu, H Li… - International Journal of …, 2021 - Springer
Purpose The robust and automatic segmentation of the pulmonary lobe is vital to surgical
planning and regional image analysis of pulmonary related diseases in real-time Computer …
planning and regional image analysis of pulmonary related diseases in real-time Computer …
[HTML][HTML] Automated lung segmentation on chest computed tomography images with extensive lung parenchymal abnormalities using a deep neural network
Objective We aimed to develop a deep neural network for segmenting lung parenchyma
with extensive pathological conditions on non-contrast chest computed tomography (CT) …
with extensive pathological conditions on non-contrast chest computed tomography (CT) …
Automatic lung segmentation in low-dose chest CT scans using convolutional deep and wide network (CDWN)
Computed tomography (CT) imaging is the preferred imaging modality for diagnosing lung-
related complaints. Automatic lung segmentation is the most common prerequisite to …
related complaints. Automatic lung segmentation is the most common prerequisite to …
Automatic lung parenchyma segmentation using a deep convolutional neural network from chest X-rays
To detect and diagnosis the lungs related diseases, a Chest X-Ray (CXR) is the major tool
used by the physician. Automated organ segmentation contributes to a crucial part of …
used by the physician. Automated organ segmentation contributes to a crucial part of …