AIMC Journal:
European radiology

Showing 621 to 630 of 646 articles

Deep-learning-based detection and segmentation of organs at risk in nasopharyngeal carcinoma computed tomographic images for radiotherapy planning.

European radiology Oct 9, 2018
OBJECTIVE: Accurate detection and segmentation of organs at risks (OARs) in CT image is the key step for efficient planning of radiation therapy for nasopharyngeal carcinoma (NPC) treatment. We develop a fully automated deep-learning-based method (te...
Male Middle Aged Deep Learning Adolescent Organ Sparing Treatments Patient Care Planning Organs at Risk Nasopharyngeal Carcinoma Aged Young Adult Humans Adult Neural Networks, Computer Sensitivity and Specificity Tomography, X-Ray Computed Female
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Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.

European radiology Oct 2, 2018
OBJECTIVE: We aimed to identify optimal machine-learning methods for preoperative differentiation of sacral chordoma (SC) and sacral giant cell tumour (SGCT) based on 3D non-enhanced computed tomography (CT) and CT-enhanced (CTE) features.
Adult Male Middle Aged ROC Curve Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Linear Models Humans Spinal Neoplasms Giant Cell Tumors Sacrum Imaging, Three-Dimensional Chordoma Support Vector Machine Diagnosis, Differential Image Interpretation, Computer-Assisted
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Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images.

European radiology Sep 25, 2018
OBJECTIVES: To predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging.
Contrast Media Magnetic Resonance Imaging Neoplasm Invasiveness Pituitary Neoplasms Adenoma Area Under Curve Cavernous Sinus Male Middle Aged Female Humans Nomograms Risk Factors Support Vector Machine Retrospective Studies Aged Adult
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Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis.

European radiology Sep 3, 2018
OBJECTIVE: To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning.
Prospective Studies Female Adult Male Neural Networks, Computer Machine Learning Algorithms Decision Support Techniques Liver Cirrhosis Support Vector Machine Decision Trees Area Under Curve Hepatitis B, Chronic Middle Aged Ultrasonography ROC Curve Logistic Models Humans
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Clear Cell Renal Cell Carcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis for Prediction of Fuhrman Nuclear Grade.

European radiology Aug 30, 2018
OBJECTIVE: To evaluate the performance of quantitative computed tomography (CT) texture analysis using different machine learning (ML) classifiers for discriminating low and high nuclear grade clear cell renal cell carcinomas (cc-RCCs).
Bayes Theorem Biopsy Data Collection Kidney Neoplasms Carcinoma, Renal Cell Nephrectomy Male Middle Aged Support Vector Machine Diagnosis, Differential Female Reproducibility of Results Humans Algorithms Aged Machine Learning Retrospective Studies Adult Tomography, X-Ray Computed
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Demystification of AI-driven medical image interpretation: past, present and future.

European radiology Aug 13, 2018
The recent explosion of 'big data' has ushered in a new era of artificial intelligence (AI) algorithms in every sphere of technological activity, including medicine, and in particular radiology. However, the recent success of AI in certain flagship a...
Humans Artificial Intelligence Technology, Radiologic Algorithms Forecasting Deep Learning Radiographic Image Interpretation, Computer-Assisted
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The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest.

European radiology Aug 7, 2018
OBJECTIVES: The preoperative prediction of the WHO grade of a meningioma is important for further treatment plans. This study aimed to assess whether texture analysis (TA) based on apparent diffusion coefficient (ADC) maps could non-invasively classi...
Male Middle Aged Decision Trees Neoplasm Staging Humans Diffusion Magnetic Resonance Imaging Machine Learning Meningioma Female Meningeal Neoplasms
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Artificial intelligence in radiology: how will we be affected?

European radiology Jul 19, 2018
Humans Diagnosis, Computer-Assisted Artificial Intelligence Radiology
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Medical students' attitude towards artificial intelligence: a multicentre survey.

European radiology Jul 6, 2018
OBJECTIVES: To assess undergraduate medical students' attitudes towards artificial intelligence (AI) in radiology and medicine.
Male Radiologists Humans Surveys and Questionnaires Female Attitude of Health Personnel Artificial Intelligence Radiology Germany Young Adult Education, Medical, Undergraduate Adult Attitude to Computers Students, Medical
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Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI.

European radiology Jun 25, 2018
OBJECTIVES: Magnetic resonance imaging (MRI) is the method of choice for imaging meningiomas. Volumetric assessment of meningiomas is highly relevant for therapy planning and monitoring. We used a multiparametric deep-learning model (DLM) on routine ...
Meningioma Middle Aged Humans Meningeal Neoplasms Deep Learning Female Image Processing, Computer-Assisted Aged Magnetic Resonance Imaging Male
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