Lung nodule detection from feature engineering to deep learning in thoracic CT images: a comprehensive review
This paper presents a systematic review of the literature focused on the lung nodule
detection in chest computed tomography (CT) images. Manual detection of lung nodules by …
detection in chest computed tomography (CT) images. Manual detection of lung nodules by …
ROI-based feature learning for efficient true positive prediction using convolutional neural network for lung cancer diagnosis
S Suresh, S Mohan - Neural Computing and Applications, 2020 - Springer
Convolutional neural network (CNN) is one of the deep structured algorithms widely applied
to analyze the ability to visualize and extract the hidden texture features of image datasets …
to analyze the ability to visualize and extract the hidden texture features of image datasets …
LGAN: Lung segmentation in CT scans using generative adversarial network
Abstract Lung segmentation in Computerized Tomography (CT) images plays an important
role in various lung disease diagnosis. Most of the current lung segmentation approaches …
role in various lung disease diagnosis. Most of the current lung segmentation approaches …
[HTML][HTML] NROI based feature learning for automated tumor stage classification of pulmonary lung nodules using deep convolutional neural networks
S Suresh, S Mohan - Journal of King Saud University-Computer and …, 2022 - Elsevier
Identifying the exact pulmonary nodule boundaries in computed tomography (CT) images
are crucial tasks to computer-aided detection systems (CADx). Segregation of CT images as …
are crucial tasks to computer-aided detection systems (CADx). Segregation of CT images as …
Monitoring of membrane integrity based on electrical measurement and deep learning
Q Wang, C Dou, C **n, X Li, J Wang… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Membrane module integrity monitoring is essential in the water treatment process. Problems
such as high cost and low sensitivity limit the development of existing detection methods. An …
such as high cost and low sensitivity limit the development of existing detection methods. An …
Deep learning the features maps for automated tumor grading of lung nodule structures using convolutional neural networks
S Supriya, M Subaji - Intelligent Decision Technologies, 2020 - content.iospress.com
Accurately identifying the exact boundary region of the pulmonary nodules in lung cancer
images are the most challenging tasks in the Computer Aided Diagnosing schemes (CADx) …
images are the most challenging tasks in the Computer Aided Diagnosing schemes (CADx) …
Lung's Segmentation Using Context-Aware Regressive Conditional GAN
After declaring COVID-19 pneumonia as a pandemic, researchers promptly advanced to
seek solutions for patients fighting this fatal disease. Computed tomography (CT) scans offer …
seek solutions for patients fighting this fatal disease. Computed tomography (CT) scans offer …
Lung Nodule Detection from Feature Engineering to Deep Learning in Thoracic CT Images: a Comprehensive Review
H Amitava, D Debangshu… - Journal of Digital …, 2020 - search.proquest.com
This paper presents a systematic review of the literature focused on the lung nodule
detection in chest computed tomography (CT) images. Manual detection of lung nodules by …
detection in chest computed tomography (CT) images. Manual detection of lung nodules by …