AIMC Topic: Solitary Pulmonary Nodule

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A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.

PloS one Jul 12, 2019
BACKGROUND: Detection of pulmonary nodules is an important aspect of an automatic detection system. Incomputer-aided diagnosis (CAD) systems, the ability to detect pulmonary nodules is highly important, which plays an important role in the diagnosis ...
Radiographic Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Multiple Pulmonary Nodules False Positive Reactions Imaging, Three-Dimensional Humans Solitary Pulmonary Nodule Reference Standards Lung Neoplasms Neural Networks, Computer Early Detection of Cancer Tomography, X-Ray Computed
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Semi-supervised adversarial model for benign-malignant lung nodule classification on chest CT.

Medical image analysis Jul 10, 2019
Classification of benign-malignant lung nodules on chest CT is the most critical step in the early detection of lung cancer and prolongation of patient survival. Despite their success in image classification, deep convolutional neural networks (DCNNs...
Humans Algorithms Tomography, X-Ray Computed Supervised Machine Learning Lung Neoplasms Precancerous Conditions Datasets as Topic Solitary Pulmonary Nodule Radiography, Thoracic Radiographic Image Interpretation, Computer-Assisted
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Classification of benign and malignant lung nodules from CT images based on hybrid features.

Physics in medicine and biology Jun 20, 2019
The classification of benign and malignant lung nodules has great significance for the early detection of lung cancer, since early diagnosis of nodules can greatly increase patient survival. In this paper, we propose a novel classification method for...
Image Processing, Computer-Assisted Lung Neoplasms Humans Solitary Pulmonary Nodule Neural Networks, Computer Algorithms Tomography, X-Ray Computed ROC Curve
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Artificial intelligence and radiomics in pulmonary nodule management: current status and future applications.

Clinical radiology Jun 12, 2019
Artificial intelligence (AI) has been present in some guise within the field of radiology for over 50 years. The first studies investigating computer-aided diagnosis in thoracic radiology date back to the 1960s, and in the subsequent years, the main ...
Humans Neural Networks, Computer Artificial Intelligence Forecasting Radiographic Image Interpretation, Computer-Assisted Lung Neoplasms Tomography, X-Ray Computed Multiple Pulmonary Nodules Diagnosis, Computer-Assisted Solitary Pulmonary Nodule Deep Learning
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Natural Language Processing for Identification of Incidental Pulmonary Nodules in Radiology Reports.

Journal of the American College of Radiology : JACR May 24, 2019
PURPOSE: To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations.
United States Solitary Pulmonary Nodule Natural Language Processing Reproducibility of Results Male Cohort Studies Radiology Research Report Incidental Findings Humans Retrospective Studies Tomography, X-Ray Computed Electronic Health Records Female
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Automated pulmonary nodule detection in CT images using 3D deep squeeze-and-excitation networks.

International journal of computer assisted radiology and surgery Apr 26, 2019
PURPOSE: Pulmonary nodule detection has great significance for early treating lung cancer and increasing patient survival. This work presents a novel automated computer-aided detection scheme for pulmonary nodules based on deep convolutional neural n...
Solitary Pulmonary Nodule Humans Neural Networks, Computer Imaging, Three-Dimensional Tomography, X-Ray Computed Lung Neoplasms Lung
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Lung nodule classification using deep Local-Global networks.

International journal of computer assisted radiology and surgery Apr 24, 2019
PURPOSE: Lung nodules have very diverse shapes and sizes, which makes classifying them as benign/malignant a challenging problem. In this paper, we propose a novel method to predict the malignancy of nodules that have the capability to analyze the sh...
Solitary Pulmonary Nodule Tomography, X-Ray Computed Image Processing, Computer-Assisted Lung Neoplasms Humans Neural Networks, Computer
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Pulmonary nodule detection in CT scans with equivariant CNNs.

Medical image analysis Mar 28, 2019
Convolutional Neural Networks (CNNs) require a large amount of annotated data to learn from, which is often difficult to obtain for medical imaging problems. In this work we show that the sample complexity of CNNs can be significantly improved by usi...
Humans Radiographic Image Interpretation, Computer-Assisted Imaging, Three-Dimensional Neural Networks, Computer Lung Neoplasms Tomography, X-Ray Computed Solitary Pulmonary Nodule Deep Learning
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Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss.

Journal of healthcare engineering Feb 4, 2019
Early detection and classification of pulmonary nodules using computer-aided diagnosis (CAD) systems is useful in reducing mortality rates of lung cancer. In this paper, we propose a new deep learning method to improve classification accuracy of pulm...
Tomography, X-Ray Computed Deep Learning Lung Neoplasms Humans Neural Networks, Computer Databases, Factual Solitary Pulmonary Nodule Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted
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Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence.

Biomedical engineering online Jan 22, 2019
BACKGROUND: A deep learning computer artificial intelligence system is helpful for early identification of ground glass opacities (GGOs).
Lung Neoplasms Solitary Pulmonary Nodule Radiology Radiographic Image Interpretation, Computer-Assisted False Positive Reactions Diagnosis, Computer-Assisted Deep Learning Humans Image Processing, Computer-Assisted Algorithms Reproducibility of Results Databases, Factual Sensitivity and Specificity Tomography, X-Ray Computed Lung
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