Deep learning applications in computed tomography images for pulmonary nodule detection and diagnosis: A review
Lung cancer has one of the highest mortality rates of all cancers and poses a severe threat
to people's health. Therefore, diagnosing lung nodules at an early stage is crucial to …
to people's health. Therefore, diagnosing lung nodules at an early stage is crucial to …
Segmentation and image analysis of abnormal lungs at CT: current approaches, challenges, and future trends
The computer-based process of identifying the boundaries of lung from surrounding thoracic
tissue on computed tomographic (CT) images, which is called segmentation, is a vital first …
tissue on computed tomographic (CT) images, which is called segmentation, is a vital first …
Inf-net: Automatic covid-19 lung infection segmentation from ct images
Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to
face an existential health crisis. Automated detection of lung infections from computed …
face an existential health crisis. Automated detection of lung infections from computed …
Automated pulmonary nodule detection in CT images using deep convolutional neural networks
Lung cancer is one of the leading causes of cancer-related death worldwide. Early
diagnosis can effectively reduce the mortality, and computer-aided diagnosis (CAD) as an …
diagnosis can effectively reduce the mortality, and computer-aided diagnosis (CAD) as an …
Lung pattern classification for interstitial lung diseases using a deep convolutional neural network
M Anthimopoulos, S Christodoulidis… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Automated tissue characterization is one of the most crucial components of a computer
aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research …
aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research …
Multilevel contextual 3-D CNNs for false positive reduction in pulmonary nodule detection
Objective: False positive reduction is one of the most crucial components in an automated
pulmonary nodule detection system, which plays an important role in lung cancer diagnosis …
pulmonary nodule detection system, which plays an important role in lung cancer diagnosis …
Lung CT image segmentation using deep neural networks
Lung CT image segmentation is a necessary initial step for lung image analysis, it is a
prerequisite step to provide an accurate lung CT image analysis such as lung cancer …
prerequisite step to provide an accurate lung CT image analysis such as lung cancer …
A 3D probabilistic deep learning system for detection and diagnosis of lung cancer using low-dose CT scans
O Ozdemir, RL Russell, AA Berlin - IEEE transactions on …, 2019 - ieeexplore.ieee.org
We introduce a new computer aided detection and diagnosis system for lung cancer
screening with low-dose CT scans that produces meaningful probability assessments. Our …
screening with low-dose CT scans that produces meaningful probability assessments. Our …
Machine-learning classification of texture features of portable chest X-ray accurately classifies COVID-19 lung infection
Background The large volume and suboptimal image quality of portable chest X-rays
(CXRs) as a result of the COVID-19 pandemic could post significant challenges for …
(CXRs) as a result of the COVID-19 pandemic could post significant challenges for …
Multisource transfer learning with convolutional neural networks for lung pattern analysis
S Christodoulidis, M Anthimopoulos… - IEEE journal of …, 2016 - ieeexplore.ieee.org
Early diagnosis of interstitial lung diseases is crucial for their treatment, but even
experienced physicians find it difficult, as their clinical manifestations are similar. In order to …
experienced physicians find it difficult, as their clinical manifestations are similar. In order to …