Review of deep learning based automatic segmentation for lung cancer radiotherapy
X Liu, KW Li, R Yang, LS Geng - Frontiers in oncology, 2021 - frontiersin.org
Lung cancer is the leading cause of cancer-related mortality for males and females.
Radiation therapy (RT) is one of the primary treatment modalities for lung cancer. While …
Radiation therapy (RT) is one of the primary treatment modalities for lung cancer. While …
A systematic review of automated segmentation methods and public datasets for the lung and its lobes and findings on computed tomography images
Objectives: Automated computational segmentation of the lung and its lobes and findings in
X-Ray based computed tomography (CT) images is a challenging problem with important …
X-Ray based computed tomography (CT) images is a challenging problem with important …
LDANet: Automatic lung parenchyma segmentation from CT images
Y Chen, L Feng, C Zheng, T Zhou, L Liu, P Liu… - Computers in Biology …, 2023 - Elsevier
Automatic segmentation of the lung parenchyma from computed tomography (CT) images is
helpful for the subsequent diagnosis and treatment of patients. In this paper, based on a …
helpful for the subsequent diagnosis and treatment of patients. In this paper, based on a …
[HTML][HTML] Optimization and fine-tuning of DenseNet model for classification of COVID-19 cases in medical imaging
T Chauhan, H Palivela, S Tiwari - International Journal of Information …, 2021 - Elsevier
It's been more than a year that the entire world is fighting against COVID-19 pandemic.
Starting from the Wuhan city in China, COVID-19 has conquered the entire world with its …
Starting from the Wuhan city in China, COVID-19 has conquered the entire world with its …
Three-stage segmentation of lung region from CT images using deep neural networks
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 …
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) …
ContactGAN development–prediction of tire-pavement contact stresses using a generative and transfer learning model
An accurate characterisation of tire-pavement contact stresses is important for pavement
structural analysis and performance evaluation. The demand for rapid pavement design and …
structural analysis and performance evaluation. The demand for rapid pavement design and …
Deep learning in structural and functional lung image analysis
The recent resurgence of deep learning (DL) has dramatically influenced the medical
imaging field. Medical image analysis applications have been at the forefront of DL research …
imaging field. Medical image analysis applications have been at the forefront of DL research …
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 …
analyze lung CT (computed tomography) images. However, traditional lung segmentation …
Искусственный интеллект в медицине: современное состояние и основные направления развития интеллектуальной диагностики
АА Мелдо, ЛВ Уткин… - Лучевая диагностика и …, 2020 - radiag.bmoc-spb.ru
Аннотация Главное отличие систем искусственного интеллекта (ИИ) от простых
автоматизированных алгоритмов заключается в способности к обучению, обобщению …
автоматизированных алгоритмов заключается в способности к обучению, обобщению …