Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
Shortly after deep learning algorithms were applied to Image Analysis, and more importantly
to medical imaging, their applications increased significantly to become a trend. Likewise …
to medical imaging, their applications increased significantly to become a trend. Likewise …
A comprehensive survey on the progress, process, and challenges of lung cancer detection and classification
MF Mridha, AR Prodeep, ASMM Hoque… - Journal of …, 2022 - Wiley Online Library
Lung cancer is the primary reason of cancer deaths worldwide, and the percentage of death
rate is increasing step by step. There are chances of recovering from lung cancer by …
rate is increasing step by step. There are chances of recovering from lung cancer by …
Label-free segmentation of COVID-19 lesions in lung CT
Scarcity of annotated images hampers the building of automated solution for reliable COVID-
19 diagnosis and evaluation from CT. To alleviate the burden of data annotation, we herein …
19 diagnosis and evaluation from CT. To alleviate the burden of data annotation, we herein …
[HTML][HTML] Prior-aware autoencoders for lung pathology segmentation
Segmentation of lung pathology in Computed Tomography (CT) images is of great
importance for lung disease screening. However, the presence of different types of lung …
importance for lung disease screening. However, the presence of different types of lung …
Deep Fuzzy SegNet-based lung nodule segmentation and optimized deep learning for lung cancer detection
Globally, lung cancer has a high fatality rate and is a lethal disease. Since lung cancer
affects both men and women, it requires extra consideration when evaluating various …
affects both men and women, it requires extra consideration when evaluating various …
Adversarial transformer network for classification of lung cancer disease from CT scan images
S Murthy, PMK Prasad - Biomedical Signal Processing and Control, 2023 - Elsevier
Lung cancer is a dreadful disease that affects both men and women; an early prognosis is
highly required to prolong human life. Recently, the computer-aided diagnosis (CAD) system …
highly required to prolong human life. Recently, the computer-aided diagnosis (CAD) system …
A novel data augmentation method using style-based GAN for robust pulmonary nodule segmentation
H Shi, J Lu, Q Zhou - 2020 Chinese Control and Decision …, 2020 - ieeexplore.ieee.org
Accurate and automatic segmentation of pulmonary nodules from computed tomography
(CT) images is an important task for lung cancer analysis. However, the scarcity and …
(CT) images is an important task for lung cancer analysis. However, the scarcity and …
Multi-granularity scale-aware networks for hard pixels segmentation of pulmonary nodules
Accurate automatic segmentation of pulmonary nodules can greatly assist in the early
clinical diagnosis and analysis of lung cancer. However, it remains a challenging task due to …
clinical diagnosis and analysis of lung cancer. However, it remains a challenging task due to …
[PDF][PDF] Anomaly detection on medical images using autoencoder and convolutional neural network
R Siddalingappa, S Kanagaraj - International Journal of Advanced …, 2021 - drive.google.com
Detection of anomalies from the medical image dataset improves prognosis by discovering
new facts hidden in the data. The present study aims to discuss anomaly detection using …
new facts hidden in the data. The present study aims to discuss anomaly detection using …
Generation of annotated brain tumor MRIs with tumor-induced tissue deformations for training and assessment of neural networks
Abstract Machine learning methods heavily rely on the availability of large annotated
datasets of a certain domain for training. However, freely available datasets of patients with …
datasets of a certain domain for training. However, freely available datasets of patients with …