AIMC Journal:
European radiology

Showing 471 to 480 of 625 articles

Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging.

European radiology Oct 14, 2020
OBJECTIVES: There currently lacks a noninvasive and accurate method to distinguish benign and malignant ovarian lesion prior to treatment. This study developed a deep learning algorithm that distinguishes benign from malignant ovarian lesion by apply...
Humans Neural Networks, Computer Artificial Intelligence Magnetic Resonance Imaging Ovarian Neoplasms Ovarian Cysts Female Sensitivity and Specificity Deep Learning
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Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique.

European radiology Oct 8, 2020
OBJECTIVES: To evaluate the image quality of low iodine concentration, dual-energy CT (DECT) combined with a deep learning-based noise reduction technique for pediatric abdominal CT, compared with standard iodine concentration single-energy polychrom...
Humans Retrospective Studies Deep Learning Young Adult Tomography, X-Ray Computed Adult Adolescent Female Male Signal-To-Noise Ratio Child, Preschool Radiography, Dual-Energy Scanned Projection Child Contrast Media
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How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts.

European radiology Oct 1, 2020
In recent years, there has been a dramatic increase in research papers about machine learning (ML) and artificial intelligence in radiology. With so many papers around, it is of paramount importance to make a proper scientific quality assessment as t...
Algorithms Reproducibility of Results Radiology Humans Artificial Intelligence Machine Learning Reading
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Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks.

European radiology Oct 1, 2020
OBJECTIVE: To explore the application of deep learning in patients with primary osteoporosis, and to develop a fully automatic method based on deep convolutional neural network (DCNN) for vertebral body segmentation and bone mineral density (BMD) cal...
Retrospective Studies Osteoporosis Tomography, X-Ray Computed Mass Screening Humans Neural Networks, Computer
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Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network.

European radiology Sep 28, 2020
OBJECTIVES: The goal of the present study was to classify the most common types of plain radiographs using a neural network and to validate the network's performance on internal and external data. Such a network could help improve various radiologica...
Deep Learning Humans Radiography Neural Networks, Computer Workflow Algorithms
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Fully automated body composition analysis in routine CT imaging using 3D semantic segmentation convolutional neural networks.

European radiology Sep 18, 2020
OBJECTIVES: Body tissue composition is a long-known biomarker with high diagnostic and prognostic value not only in cardiovascular, oncological, and orthopedic diseases but also in rehabilitation medicine or drug dosage. In this study, the aim was to...
Semantics Humans Neural Networks, Computer Image Processing, Computer-Assisted Tomography, X-Ray Computed Abdomen Body Composition
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Applications of artificial intelligence (AI) in diagnostic radiology: a technography study.

European radiology Sep 18, 2020
OBJECTIVES: Why is there a major gap between the promises of AI and its applications in the domain of diagnostic radiology? To answer this question, we systematically review and critically analyze the AI applications in the radiology domain.
Radiology Workflow Artificial Intelligence Forecasting Radiography
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Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients.

European radiology Sep 18, 2020
OBJECTIVE: To evaluate whether the initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19.
COVID-19 Prognosis Retrospective Studies SARS-CoV-2 Tomography, X-Ray Computed Humans Hospitalization Aged Intensive Care Units Artificial Intelligence Pulmonary Disease, Chronic Obstructive Female Radiography Emergency Service, Hospital Italy Neurodegenerative Diseases Coronary Artery Disease Sex Factors Severity of Illness Index Deep Learning Age Factors Male Middle Aged Comorbidity Proportional Hazards Models Radiography, Thoracic Mortality
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Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network.

European radiology Sep 3, 2020
OBJECTIVES: The current study aimed to design an ultra-low-dose CT examination protocol using a deep learning approach suitable for clinical diagnosis of COVID-19 patients.
Image Processing, Computer-Assisted Radiation Dosage Signal-To-Noise Ratio Reproducibility of Results SARS-CoV-2 Deep Learning Humans Algorithms Tomography, X-Ray Computed Neural Networks, Computer COVID-19
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T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology.

European radiology Sep 2, 2020
OBJECTIVES: To explore the associations between T1 and T2 magnetic resonance fingerprinting (MRF) measurements and corresponding tissue compartment ratios (TCRs) on whole mount histopathology of prostate cancer (PCa) and prostatitis.
Epithelium Diffusion Magnetic Resonance Imaging Prostatitis Humans Retrospective Studies Male Deep Learning Magnetic Resonance Imaging Prostatic Neoplasms
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