Recent advancements in deep learning based lung cancer detection: A systematic review
Cancer is considered to be a key cause of substantial fatality and morbidity in the world. A
report from the International Agency for Research on Cancer (IARC) states that 27 million …
report from the International Agency for Research on Cancer (IARC) states that 27 million …
Automatic 3D pulmonary nodule detection in CT images: a survey
This work presents a systematic review of techniques for the 3D automatic detection of
pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze …
pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze …
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 …
Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks
We propose a novel Computer-Aided Detection (CAD) system for pulmonary nodules using
multi-view convolutional networks (ConvNets), for which discriminative features are …
multi-view convolutional networks (ConvNets), for which discriminative features are …
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 …
Improving computer-aided detection using convolutional neural networks and random view aggregation
Automated computer-aided detection (CADe) has been an important tool in clinical practice
and research. State-of-the-art methods often show high sensitivities at the cost of high false …
and research. State-of-the-art methods often show high sensitivities at the cost of high false …
[PDF][PDF] Lung cancer detection and classification with 3D convolutional neural network (3D-CNN)
This paper demonstrates a computer-aided diagnosis (CAD) system for lung cancer
classification of CT scans with unmarked nodules, a dataset from the Kaggle Data Science …
classification of CT scans with unmarked nodules, a dataset from the Kaggle Data Science …
Lung nodule detection based on faster R-CNN framework
Y Su, D Li, X Chen - Computer Methods and Programs in Biomedicine, 2021 - Elsevier
Background Lung cancer is a worldwide high-risk disease, and lung nodules are the main
manifestation of early lung cancer. Automatic detection of lung nodules reduces the …
manifestation of early lung cancer. Automatic detection of lung nodules reduces the …
Computer-aided detection (CADe) and diagnosis (CADx) system for lung cancer with likelihood of malignancy
M Firmino, G Angelo, H Morais, MR Dantas… - Biomedical engineering …, 2016 - Springer
Abstract Background CADe and CADx systems for the detection and diagnosis of lung
cancer have been important areas of research in recent decades. However, these areas are …
cancer have been important areas of research in recent decades. However, these areas are …
Multi-view multi-scale CNNs for lung nodule type classification from CT images
In this paper, we propose a novel convolution neural networks (CNNs) based method for
nodule type classification. Compared with classical approaches that are handling four solid …
nodule type classification. Compared with classical approaches that are handling four solid …