AIMC Journal:
European radiology

Showing 501 to 510 of 636 articles

From community-acquired pneumonia to COVID-19: a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans.

European radiology Jul 18, 2020
OBJECTIVE: To develop a fully automated AI system to quantitatively assess the disease severity and disease progression of COVID-19 using thick-section chest CT images.
China ROC Curve Pneumonia Coronavirus Infections Community-Acquired Infections Betacoronavirus Male Middle Aged Disease Progression Lung Deep Learning Pneumonia, Viral Humans Artificial Intelligence Pandemics COVID-19 Retrospective Studies Tomography, X-Ray Computed Female SARS-CoV-2
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Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features.

European radiology Jul 16, 2020
OBJECTIVES: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus...
Aged Aged, 80 and over Adult Male Middle Aged Treatment Outcome Humans Machine Learning Algorithms Retrospective Studies Reproducibility of Results Prostate Biopsy Prostatectomy Diffusion Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging Support Vector Machine Cluster Analysis Principal Component Analysis Area Under Curve Prostatic Neoplasms
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Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration.

European radiology Jul 14, 2020
OBJECTIVES: To evaluate the calibration of a deep learning (DL) model in a diagnostic cohort and to improve model's calibration through recalibration procedures.
Calibration Reference Standards Radiography, Thoracic Image Processing, Computer-Assisted Predictive Value of Tests Area Under Curve Bayes Theorem Pattern Recognition, Automated Algorithms Retrospective Studies Female Reproducibility of Results Aged Adult Male Middle Aged Lung Diagnosis, Computer-Assisted Deep Learning ROC Curve Humans
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A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images.

European radiology Jul 2, 2020
OBJECTIVES: To utilize a deep learning model for automatic detection of abnormalities in chest CT images from COVID-19 patients and compare its quantitative determination performance with radiological residents.
Humans Pandemics COVID-19 Lung Deep Learning China Algorithms Tomography, X-Ray Computed Female Coronavirus Infections SARS-CoV-2 Betacoronavirus Male Pneumonia, Viral Middle Aged
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Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis.

European radiology Jun 30, 2020
OBJECTIVES: The aim of this study was to systematically review the literature and perform a meta-analysis of machine learning (ML) diagnostic accuracy studies focused on clinically significant prostate cancer (csPCa) identification on MRI.
Reference Standards Prostatectomy Diagnosis, Computer-Assisted ROC Curve Magnetic Resonance Imaging Humans Area Under Curve Machine Learning Prostatic Neoplasms Biopsy Algorithms Male Prevalence
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Emphysema quantification using low-dose computed tomography with deep learning-based kernel conversion comparison.

European radiology Jun 29, 2020
OBJECTIVE: This study determined the effect of dose reduction and kernel selection on quantifying emphysema using low-dose computed tomography (LDCT) and evaluated the efficiency of a deep learning-based kernel conversion technique in normalizing ker...
Radiation Dosage Biometry Humans Diagnosis, Computer-Assisted Retrospective Studies Deep Learning Tomography, X-Ray Computed Treatment Outcome Female Lung Diseases Aged Pulmonary Emphysema Cross-Sectional Studies Male Middle Aged Lung
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Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

European radiology Jun 27, 2020
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
Sex Factors Diagnostic Tests, Routine Humans Observer Variation Algorithms Pattern Recognition, Automated Retrospective Studies Calibration Tomography, X-Ray Computed Adenocarcinoma of Lung ROC Curve Female Adult Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Logistic Models Nomograms Age Factors Solitary Pulmonary Nodule Regression Analysis Diagnosis, Differential Granuloma Tuberculosis
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Using decision curve analysis to benchmark performance of a magnetic resonance imaging-based deep learning model for prostate cancer risk assessment.

European radiology Jun 26, 2020
OBJECTIVES: To benchmark the performance of a calibrated 3D convolutional neural network (CNN) applied to multiparametric MRI (mpMRI) for risk assessment of clinically significant prostate cancer (csPCa) using decision curve analysis (DCA).
Humans Machine Learning Algorithms Retrospective Studies Male Risk Assessment Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Benchmarking Prostatic Neoplasms Prostate-Specific Antigen Observer Variation Biopsy Calibration Normal Distribution
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Machine learning-based CT texture analysis to predict HPV status in oropharyngeal squamous cell carcinoma: comparison of 2D and 3D segmentation.

European radiology Jun 26, 2020
OBJECTIVE: To compare the CT texture feature reproducibility of 2D and 3D segmentations and their machine learning (ML)-based classifications for predicting human papilloma virus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC).
Male Imaging, Three-Dimensional Image Processing, Computer-Assisted Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Regression Analysis Diagnosis, Differential Area Under Curve Observer Variation Alphapapillomavirus Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Humans
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Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning-based filter using convolutional neural network.

European radiology Jun 17, 2020
OBJECTIVES: To reveal the utility of motion artifact reduction with convolutional neural network (MARC) in gadoxetate disodium-enhanced multi-arterial phase MRI of the liver.
Magnetic Resonance Imaging Artifacts Breath Holding Gadolinium DTPA Adult Male Middle Aged Deep Learning Liver Neoplasms Contrast Media Neural Networks, Computer Retrospective Studies Female Aged Aged, 80 and over Humans
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