Computer‐aided diagnosis systems for lung cancer: challenges and methodologies
A El-Baz, GM Beache, G Gimel′ farb… - … journal of biomedical …, 2013 - Wiley Online Library
This paper overviews one of the most important, interesting, and challenging problems in
oncology, the problem of lung cancer diagnosis. Developing an effective computer-aided …
oncology, the problem of lung cancer diagnosis. Developing an effective computer-aided …
[HTML][HTML] Computer-aided detection system for lung cancer in computed tomography scans: review and future prospects
M Firmino, AH Morais, RM Mendoça… - Biomedical engineering …, 2014 - Springer
Introduction The goal of this paper is to present a critical review of major Computer-Aided
Detection systems (CADe) for lung cancer in order to identify challenges for future research …
Detection systems (CADe) for lung cancer in order to identify challenges for future research …
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 …
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge
Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has
been an active area of research for the last two decades. However, there have only been …
been an active area of research for the last two decades. However, there have only been …
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 nodule detection in CT images using deep convolutional neural networks
R Golan, C Jacob, J Denzinger - 2016 international joint …, 2016 - ieeexplore.ieee.org
Early detection of lung nodules in thoracic Computed Tomography (CT) scans is of great
importance for the successful diagnosis and treatment of lung cancer. Due to improvements …
importance for the successful diagnosis and treatment of lung cancer. Due to improvements …
Automatic lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy in chest CTs
Y Gu, X Lu, L Yang, B Zhang, D Yu, Y Zhao… - Computers in biology …, 2018 - Elsevier
Objective A novel computer-aided detection (CAD) scheme for lung nodule detection using
a 3D deep convolutional neural network combined with a multi-scale prediction strategy is …
a 3D deep convolutional neural network combined with a multi-scale prediction strategy is …
An automatic detection system of lung nodule based on multigroup patch-based deep learning network
High-efficiency lung nodule detection dramatically contributes to the risk assessment of lung
cancer. It is a significant and challenging task to quickly locate the exact positions of lung …
cancer. It is a significant and challenging task to quickly locate the exact positions of lung …
[HTML][HTML] Segmentation of lung nodules using improved 3D-UNet neural network
Lung cancer has one of the highest morbidity and mortality rates in the world. Lung nodules
are an early indicator of lung cancer. Therefore, accurate detection and image segmentation …
are an early indicator of lung cancer. Therefore, accurate detection and image segmentation …
SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis
Breast cancer is the second leading cause of cancer death among women worldwide.
Nevertheless, it is also one of the most treatable malignances if detected early. Screening for …
Nevertheless, it is also one of the most treatable malignances if detected early. Screening for …