AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Detection of pulmonary nodules based on a multiscale feature 3D U-Net convolutional neural network of transfer learning.

PloS one Aug 26, 2020
A new computer-aided detection scheme is proposed, the 3D U-Net convolutional neural network, based on multiscale features of transfer learning to automatically detect pulmonary nodules from the thoracic region containing background and noise. The te...
Imaging, Three-Dimensional Lung Neoplasms Solitary Pulmonary Nodule Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Machine Learning Algorithms Tomography, X-Ray Computed Lung
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Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs.

Journal of healthcare engineering Aug 24, 2020
The early screening and diagnosis of tuberculosis plays an important role in the control and treatment of tuberculosis infections. In this paper, an integrated computer-aided system based on deep learning is proposed for the detection of multiple cat...
Reproducibility of Results False Positive Reactions Humans ROC Curve Radiography, Thoracic Sensitivity and Specificity Neural Networks, Computer Area Under Curve Thorax Diagnosis, Computer-Assisted Algorithms Equipment Design X-Rays Databases, Factual Deep Learning Radiographic Image Interpretation, Computer-Assisted Computer Systems Tuberculosis, Pulmonary
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Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank.

IEEE journal of biomedical and health informatics Aug 20, 2020
Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide since first reported. Timely diagnosis of COVID-19 is crucial both for disease control and patient care. Non-contrast thoracic computed tomography (CT) has been identified as an effecti...
COVID-19 Testing Clinical Laboratory Techniques Betacoronavirus Pneumonia, Viral Retrospective Studies Tomography, X-Ray Computed SARS-CoV-2 Diagnostic Errors Humans Deep Learning Neural Networks, Computer Cohort Studies Pandemics Computational Biology COVID-19 Radiographic Image Interpretation, Computer-Assisted Algorithms Supervised Machine Learning Coronavirus Infections
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Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem.

European radiology experimental Aug 20, 2020
BACKGROUND: Automated segmentation of anatomical structures is a crucial step in image analysis. For lung segmentation in computed tomography, a variety of approaches exists, involving sophisticated pipelines trained and validated on different datase...
Tomography, X-Ray Computed Reproducibility of Results Deep Learning Radiographic Image Interpretation, Computer-Assisted Lung Diseases Humans Datasets as Topic
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Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.

Nature communications Aug 14, 2020
Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other ...
Algorithms Tomography, X-Ray Computed Female SARS-CoV-2 Aged Humans Artificial Intelligence Pandemics COVID-19 Imaging, Three-Dimensional Radiographic Image Interpretation, Computer-Assisted Coronavirus Infections COVID-19 Testing Clinical Laboratory Techniques Betacoronavirus Pneumonia, Viral Lung Aged, 80 and over Deep Learning Young Adult Adolescent Adult Child, Preschool Male Child Middle Aged
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New convolutional neural network model for screening and diagnosis of mammograms.

PloS one Aug 13, 2020
Breast cancer is the most common cancer in women and poses a great threat to women's life and health. Mammography is an effective method for the diagnosis of breast cancer, but the results are largely limited by the clinical experience of radiologist...
Datasets as Topic Mass Screening Early Detection of Cancer Mammography Radiographic Image Interpretation, Computer-Assisted Humans Breast Databases, Factual Female Breast Neoplasms Deep Learning
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3D Automatic Segmentation of Aortic Computed Tomography Angiography Combining Multi-View 2D Convolutional Neural Networks.

Cardiovascular engineering and technology Aug 11, 2020
PURPOSE: The quantitative analysis of contrast-enhanced Computed Tomography Angiography (CTA) is essential to assess aortic anatomy, identify pathologies, and perform preoperative planning in vascular surgery. To overcome the limitations given by man...
Humans Imaging, Three-Dimensional Retrospective Studies Computed Tomography Angiography Predictive Value of Tests Female Aortography Aortic Aneurysm, Abdominal Aged Radiographic Image Interpretation, Computer-Assisted Aged, 80 and over Aorta, Abdominal Male Middle Aged Deep Learning
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Effect of vessel wall segmentation on volumetric and radiomic parameters of coronary plaques with adverse characteristics.

Journal of cardiovascular computed tomography Aug 10, 2020
BACKGROUND: Quantitative coronary plaque parameters are increasingly being utilized as surrogate endpoints of pharmaceutical trials. However, little is known whether differences in segmentation significantly alter parameter values.
Coronary Vessels Aged Plaque, Atherosclerotic Male Vascular Calcification Middle Aged Humans Computed Tomography Angiography Severity of Illness Index Predictive Value of Tests Machine Learning Coronary Angiography Retrospective Studies Clinical Competence Radiographic Image Interpretation, Computer-Assisted Female Coronary Artery Disease Reproducibility of Results Observer Variation
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Artificial Intelligence Solutions for Analysis of X-ray Images.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Aug 6, 2020
Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care and enhance the value of radiology in patient care and population health. The potential opportunity of AI to aid in triage and interpretation of conve...
Radiographic Image Interpretation, Computer-Assisted Lung Diseases Musculoskeletal Diseases Radiography, Thoracic Musculoskeletal System Humans Artificial Intelligence Radiography
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Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST).

PloS one Aug 3, 2020
BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that annual screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. Nonetheless, the leading cause of mortality in the study was from...
Risk Assessment Lung Lung Neoplasms Fatty Liver United States Mass Screening Early Detection of Cancer Liver Randomized Controlled Trials as Topic Cigarette Smoking Radiographic Image Interpretation, Computer-Assisted Female Coronary Vessels Humans Risk Factors Clinical Trials, Phase III as Topic Machine Learning Male National Cancer Institute (U.S.) Retrospective Studies Cardiovascular Diseases Emphysema Tomography, X-Ray Computed Middle Aged
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