AIMC Journal:
European radiology

Showing 581 to 590 of 646 articles

Deep learning with ultrasonography: automated classification of liver fibrosis using a deep convolutional neural network.

European radiology Sep 2, 2019
OBJECTIVES: The aim of this study was to develop a deep convolutional neural network (DCNN) for the prediction of the METAVIR score using B-mode ultrasonography images.
Algorithms Retrospective Studies Female Reproducibility of Results Humans Ultrasonography ROC Curve Liver Cirrhosis Radiologists Elasticity Imaging Techniques Male Middle Aged Deep Learning Clinical Competence
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Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.

European radiology Aug 29, 2019
OBJECTIVE: To investigate the discriminative capabilities of different machine learning-based classification models on the differentiation of small (< 4 cm) renal angiomyolipoma without visible fat (AMLwvf) and renal cell carcinoma (RCC).
Carcinoma, Renal Cell Angiomyolipoma Middle Aged Case-Control Studies Diagnosis, Differential Kidney Neoplasms Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Aged Male
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Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network.

European radiology Aug 29, 2019
OBJECTIVE: To present a deep learning-based approach for semi-automatic prostate cancer classification based on multi-parametric magnetic resonance (MR) imaging using a 3D convolutional neural network (CNN).
Male Deep Learning ROC Curve Area Under Curve Prostatic Neoplasms Biopsy Diffusion Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging Humans Sensitivity and Specificity
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Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules.

European radiology Aug 23, 2019
PURPOSE: To enhance clinician's decision-making by diagnosing hepatocellular carcinoma (HCC) in cirrhotic patients with indeterminate liver nodules using quantitative imaging features extracted from triphasic CT scans.
Humans Artificial Intelligence Machine Learning Liver Cirrhosis Contrast Media Male Liver Middle Aged Diagnosis, Differential Liver Neoplasms Carcinoma, Hepatocellular Retrospective Studies Tomography, X-Ray Computed Female Aged
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Identification of suspicious invasive placentation based on clinical MRI data using textural features and automated machine learning.

European radiology Aug 23, 2019
OBJECTIVE: The aim of this study was to investigate whether intraplacental texture features from routine placental MRI can objectively and accurately predict invasive placentation.
Pregnancy Female Young Adult Adult Humans Machine Learning Algorithms Retrospective Studies Placenta Previa Magnetic Resonance Imaging Placenta Placentation Prenatal Diagnosis
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How and why should the radiologist look at the placenta?

European radiology Aug 7, 2019
This editorial comment refers to the article "Identification of suspicious invasive placentation based on clinical MRI data using textural features and automated machine learning" by Sun et al. in European Radiology. KEY POINTS: • Understanding how t...
Magnetic Resonance Imaging Humans Placenta Radiologists Machine Learning Pregnancy Female
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Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging.

European radiology Jul 22, 2019
BACKGROUND: We attempted to train and validate a model of deep learning for the preoperative prediction of the response of patients with intermediate-stage hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE).
Liver Neoplasms Humans Carcinoma, Hepatocellular Retrospective Studies Chemoembolization, Therapeutic Male Tomography, X-Ray Computed Middle Aged Female Disease Progression Deep Learning
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Deep learning to differentiate parkinsonian disorders separately using single midsagittal MR imaging: a proof of concept study.

European radiology Jul 1, 2019
OBJECTIVES: To evaluate the diagnostic performance of deep learning with the convolutional neural networks (CNN) to distinguish each representative parkinsonian disorder using MRI.
Neural Networks, Computer Retrospective Studies Female Aged Supranuclear Palsy, Progressive Aged, 80 and over Adult Male Deep Learning Middle Aged Humans Diagnosis, Differential ROC Curve Parkinsonian Disorders Magnetic Resonance Imaging Proof of Concept Study Parkinson Disease Multiple System Atrophy
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Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.

European radiology Jun 21, 2019
OBJECTIVES: The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated constru...
Middle Aged Pregnancy Radiation Dosage Humans Radiometry Neural Networks, Computer Female Radiography, Abdominal Monte Carlo Method Computer Simulation Young Adult Phantoms, Imaging Tomography, X-Ray Computed Adult
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Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists.

European radiology Jun 11, 2019
OBJECTIVE: The purpose of this study was: To test whether machine learning classifiers for transition zone (TZ) and peripheral zone (PZ) can correctly classify prostate tumors into those with/without a Gleason 4 component, and to compare the performa...
Clinical Competence Area Under Curve Prostatic Neoplasms Radiologists Neoplasm Grading Humans Retrospective Studies Biopsy Machine Learning Sensitivity and Specificity Image Interpretation, Computer-Assisted Male Diffusion Magnetic Resonance Imaging Middle Aged
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