AIMC Journal:
European journal of radiology

Showing 261 to 270 of 296 articles

Differential Diagnosis of Benign and Malignant Thyroid Nodules Using Deep Learning Radiomics of Thyroid Ultrasound Images.

European journal of radiology Apr 12, 2020
PURPOSE: We aimed to propose a highly automatic and objective model named deep learning Radiomics of thyroid (DLRT) for the differential diagnosis of benign and malignant thyroid nodules from ultrasound (US) images.
Female Reproducibility of Results Male Middle Aged Humans Retrospective Studies Thyroid Nodule ROC Curve Diagnosis, Differential Area Under Curve Image Interpretation, Computer-Assisted Deep Learning Thyroid Gland Cohort Studies Ultrasonography
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Application of artificial intelligence in cardiac CT: From basics to clinical practice.

European journal of radiology Apr 8, 2020
Research into the possibilities of AI in cardiac CT has been growing rapidly in the last decade. With the rise of publicly available databases and AI algorithms, many researchers and clinicians have started investigations into the use of AI in the cl...
Algorithms Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Heart Heart Diseases Humans Artificial Intelligence
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Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours.

European journal of radiology Mar 2, 2020
PURPOSE: To evaluate the performance of machine-learning-based computed tomography (CT) radiomic analysis to differentiate high-risk thymic epithelial tumours (TETs) from low-risk TETs according to the WHO classification.
ROC Curve Area Under Curve Image Interpretation, Computer-Assisted Neoplasms, Glandular and Epithelial Young Adult Adult Male Middle Aged Thymus Neoplasms Thymus Gland Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Aged
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A machine learning model to precisely immunohistochemically classify pituitary adenoma subtypes with radiomics based on preoperative magnetic resonance imaging.

European journal of radiology Feb 13, 2020
PURPOSE: The type of pituitary adenoma (PA) cannot be clearly recognized with preoperative magnetic resonance imaging (MRI) but can be classified with immunohistochemical staining after surgery. In this study, a model to precisely immunohistochemical...
Preoperative Care Pituitary Gland Middle Aged Adolescent Magnetic Resonance Imaging Pituitary Neoplasms Adenoma Bayes Theorem Image Interpretation, Computer-Assisted Immunohistochemistry Aged Humans Young Adult Machine Learning Adult Retrospective Studies Male Female
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Towards automated generation of curated datasets in radiology: Application of natural language processing to unstructured reports exemplified on CT for pulmonary embolism.

European journal of radiology Feb 6, 2020
PURPOSE: To design and evaluate a self-trainable natural language processing (NLP)-based procedure to classify unstructured radiology reports. The method enabling the generation of curated datasets is exemplified on CT pulmonary angiogram (CTPA) repo...
Datasets as Topic Pulmonary Artery Natural Language Processing Area Under Curve Neural Networks, Computer Pulmonary Embolism Retrospective Studies Humans Female Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Aged Male Support Vector Machine
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Convolutional neural network-automated hepatobiliary phase adequacy evaluation may optimize examination time.

European journal of radiology Jan 14, 2020
PURPOSE: To develop and evaluate the performance of a fully-automated convolutional neural network (CNN)-based algorithm to evaluate hepatobiliary phase (HBP) adequacy of gadoxetate disodium (EOB)-enhanced MRI. Secondarily, we explored the potential ...
Efficiency ROC Curve Liver Neoplasms Contrast Media Magnetic Resonance Imaging Liver Area Under Curve Workflow Humans Aged Adult Image Interpretation, Computer-Assisted Male Time Neural Networks, Computer Middle Aged Gadolinium DTPA Algorithms Retrospective Studies Female
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A two-step automated quality assessment for liver MR images based on convolutional neural network.

European journal of radiology Jan 9, 2020
PURPOSE: To propose an automatic approach based on a convolutional neural network (CNN) to evaluate the quality of T2-weighted liver magnetic resonance (MR) images as nondiagnostic (ND) or diagnostic (D).
ROC Curve Magnetic Resonance Imaging Liver Image Interpretation, Computer-Assisted Neural Networks, Computer Liver Diseases Retrospective Studies Humans Reproducibility of Results Sensitivity and Specificity
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Artificial intelligence applications for thoracic imaging.

European journal of radiology Dec 11, 2019
Artificial intelligence is a hot topic in medical imaging. The development of deep learning methods and in particular the use of convolutional neural networks (CNNs), have led to substantial performance gain over the classic machine learning techniqu...
Humans Artificial Intelligence Early Detection of Cancer Radiologists Radiography, Thoracic Thorax Machine Learning Algorithms Deep Learning Lung Neoplasms
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Ethical considerations in artificial intelligence.

European journal of radiology Nov 23, 2019
With artificial intelligence (AI) precipitously perched at the apex of the hype curve, the promise of transforming the disparate fields of healthcare, finance, journalism, and security and law enforcement, among others, is enormous. For healthcare - ...
Radiologists Humans Workflow Artificial Intelligence Forecasting Radiology
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Machine learning-based multiparametric MRI radiomics for predicting the aggressiveness of papillary thyroid carcinoma.

European journal of radiology Nov 20, 2019
PURPOSE: To investigate the predictive capability of machine learning-based multiparametric magnetic resonance (MR) imaging radiomics for evaluating the aggressiveness of papillary thyroid carcinoma (PTC) preoperatively.
Diffusion Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging Thyroid Neoplasms ROC Curve Neck Prospective Studies Humans Adult Prognosis Thyroid Cancer, Papillary Machine Learning Male Female Middle Aged Young Adult Cohort Studies
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