AIMC Topic: Solitary Pulmonary Nodule

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Performance and educational training of radiographers in lung nodule or mass detection: Retrospective comparison with different deep learning algorithms.

Medicine Jun 11, 2021
The aim of this investigation was to compare the diagnostic performance of radiographers and deep learning algorithms in pulmonary nodule/mass detection on chest radiograph.A test set of 100 chest radiographs containing 53 cases with no pathology (no...
Middle Aged Lung Deep Learning Female Sensitivity and Specificity Male Solitary Pulmonary Nodule Taiwan Radiologists Radiography, Thoracic Burnout, Professional Clinical Competence Multiple Pulmonary Nodules Humans Algorithms
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Integrity of clinical information in radiology reports documenting pulmonary nodules.

Journal of the American Medical Informatics Association : JAMIA Jan 15, 2021
OBJECTIVE: Quantify the integrity, measured as completeness and concordance with a thoracic radiologist, of documenting pulmonary nodule characteristics in CT reports and assess impact on making follow-up recommendations.
Retrospective Studies Tomography, X-Ray Computed Electronic Health Records Humans Natural Language Processing Documentation Radiology Information Systems Radiography, Thoracic Middle Aged Multiple Pulmonary Nodules Female Solitary Pulmonary Nodule Aged Male
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Risk-Stratifying Pulmonary Nodules.

American journal of respiratory and critical care medicine Jan 1, 2021
Humans Deep Learning Multiple Pulmonary Nodules Solitary Pulmonary Nodule
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Diagnostic classification of solitary pulmonary nodules using support vector machine model based on 2-[18F]fluoro-2-deoxy-D-glucose PET/computed tomography texture features.

Nuclear medicine communications Jun 1, 2020
PURPOSE: This study aimed to evaluate the diagnostic value of a support vector machine (SVM) model built with texture features based on standard 2-[F]fluoro-2-deoxy-D-glucose (F-FDG) PET in patients with solitary pulmonary nodules (SPNs) at a volume ...
Solitary Pulmonary Nodule ROC Curve Positron Emission Tomography Computed Tomography Image Processing, Computer-Assisted Tumor Burden Female Humans Support Vector Machine Male Fluorodeoxyglucose F18 Retrospective Studies Middle Aged
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Lung Nodule Detection from Feature Engineering to Deep Learning in Thoracic CT Images: a Comprehensive Review.

Journal of digital imaging Jun 1, 2020
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 the radiologist is a sequential and time-consuming process. The detection is ...
Solitary Pulmonary Nodule Lung Deep Learning Lung Neoplasms Humans Tomography, X-Ray Computed
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Lung Nodule Detection in CT Images Using a Raw Patch-Based Convolutional Neural Network.

Journal of digital imaging Dec 1, 2019
Remarkable progress has been made in image classification and segmentation, due to the recent study of deep convolutional neural networks (CNNs). To solve the similar problem of diagnostic lung nodule detection in low-dose computed tomography (CT) sc...
Tomography, X-Ray Computed Lung Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Databases, Factual
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Computer-Aided Diagnosis (CAD) of Pulmonary Nodule of Thoracic CT Image Using Transfer Learning.

Journal of digital imaging Dec 1, 2019
Computer-aided diagnosis (CAD) has already been widely used in medical image processing. We recently make another trial to implement convolutional neural network (CNN) on the classification of pulmonary nodules of thoracic CT images. The biggest chal...
Humans Lung Neoplasms Reproducibility of Results Multiple Pulmonary Nodules Machine Learning Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Solitary Pulmonary Nodule Lung Databases, Factual Tomography, X-Ray Computed
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[Research progress on computed tomography image detection and classification of pulmonary nodule based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2019
Computer-aided diagnosis based on computed tomography (CT) image can realize the detection and classification of pulmonary nodules, and improve the survival rate of early lung cancer, which has important clinical significance. In recent years, with t...
Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Reproducibility of Results Deep Learning Humans
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Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Deep learning has made spectacular achievements in analysing natural images, but it faces challenges for medical applications partly due to inadequate images.
ROC Curve Reproducibility of Results Lung Neoplasms Humans Lung Solitary Pulmonary Nodule Databases, Factual Deep Learning Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed
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Expert knowledge-infused deep learning for automatic lung nodule detection.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Computer aided detection (CADe) of pulmonary nodules from computed tomography (CT) is crucial for early diagnosis of lung cancer. Self-learned features obtained by training datasets via deep learning have facilitated CADe of the nodules. ...
Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Tomography, X-Ray Computed Sensitivity and Specificity Deep Learning Humans Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Knowledge Bases
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