AIMC Journal:
European radiology

Showing 391 to 400 of 621 articles

Diagnosing autism spectrum disorder in children using conventional MRI and apparent diffusion coefficient based deep learning algorithms.

European radiology Sep 4, 2021
OBJECTIVE: To develop and validate deep learning (DL) methods for diagnosing autism spectrum disorder (ASD) based on conventional MRI (cMRI) and apparent diffusion coefficient (ADC) images.
Humans Child Autism Spectrum Disorder Deep Learning Magnetic Resonance Imaging Algorithms Diffusion Magnetic Resonance Imaging
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Deep learning radiomic nomogram to predict recurrence in soft tissue sarcoma: a multi-institutional study.

European radiology Aug 27, 2021
OBJECTIVES: To evaluate the performance of a deep learning radiomic nomogram (DLRN) model at predicting tumor relapse in patients with soft tissue sarcomas (STS) who underwent surgical resection.
Humans Deep Learning Nomograms Retrospective Studies Sarcoma Magnetic Resonance Imaging Neoplasm Recurrence, Local
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A deep learning-machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors.

European radiology Aug 25, 2021
OBJECTIVES: To build and validate deep learning and machine learning fusion models to classify benign, malignant, and intermediate bone tumors based on patient clinical characteristics and conventional radiographs of the lesion.
Bone Neoplasms Retrospective Studies Radiography Female Young Adult Adult Humans Deep Learning Machine Learning
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Molecular subtyping of diffuse gliomas using magnetic resonance imaging: comparison and correlation between radiomics and deep learning.

European radiology Aug 21, 2021
OBJECTIVES: The molecular subtyping of diffuse gliomas is important. The aim of this study was to establish predictive models based on preoperative multiparametric MRI.
Glioma Magnetic Resonance Imaging Magnetic Resonance Spectroscopy Humans Retrospective Studies Deep Learning
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Dose reduction potential of vendor-agnostic deep learning model in comparison with deep learning-based image reconstruction algorithm on CT: a phantom study.

European radiology Aug 14, 2021
OBJECTIVES: To compare the dose reduction potential (DRP) of a vendor-agnostic deep learning model (DLM, ClariCT.AI) with that of a vendor-specific deep learning-based image reconstruction algorithm (DLR, TrueFidelity™).
Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Tomography, X-Ray Computed Deep Learning Phantoms, Imaging Drug Tapering Humans Algorithms
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Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance.

European radiology Aug 12, 2021
OBJECTIVES: To evaluate if artificial intelligence (AI) can discriminate recalled benign from recalled malignant mammographic screening abnormalities to improve screening performance.
Humans Artificial Intelligence Retrospective Studies Mammography Negotiating Deep Learning Female Mass Screening Breast Neoplasms Early Detection of Cancer
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Deep learning in knee imaging: a systematic review utilizing a Checklist for Artificial Intelligence in Medical Imaging (CLAIM).

European radiology Aug 4, 2021
PURPOSE: Our purposes were (1) to explore the methodologic quality of the studies on the deep learning in knee imaging with CLAIM criterion and (2) to offer our vision for the development of CLAIM to assure high-quality reports about the application ...
Knee Joint Checklist Deep Learning Radiography Artificial Intelligence Humans Retrospective Studies
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CT-based thermometry with virtual monoenergetic images by dual-energy of fat, muscle and bone using FBP, iterative and deep learning-based reconstruction.

European radiology Jul 29, 2021
OBJECTIVES: The aim of this study was to evaluate the sensitivity of CT-based thermometry for clinical applications regarding a three-component tissue phantom of fat, muscle and bone. Virtual monoenergetic images (VMI) by dual-energy measurements and...
Radiographic Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Humans Tomography, X-Ray Computed Thermometry Algorithms Muscles Retrospective Studies Deep Learning
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Deep learning to automate the labelling of head MRI datasets for computer vision applications.

European radiology Jul 20, 2021
OBJECTIVES: The purpose of this study was to build a deep learning model to derive labels from neuroradiology reports and assign these to the corresponding examinations, overcoming a bottleneck to computer vision model development.
Area Under Curve Radiography Humans Radiologists Deep Learning Magnetic Resonance Imaging
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Value of a deep learning-based algorithm for detecting Lung-RADS category 4 nodules on chest radiographs in a health checkup population: estimation of the sample size for a randomized controlled trial.

European radiology Jul 15, 2021
OBJECTIVE: To explore the value of a deep learning-based algorithm in detecting Lung CT Screening Reporting and Data System category 4 nodules on chest radiographs from an asymptomatic health checkup population.
Radiography, Thoracic Lung Neoplasms Sample Size Radiographic Image Interpretation, Computer-Assisted Lung Deep Learning Retrospective Studies Tomography, X-Ray Computed Sensitivity and Specificity Humans Algorithms
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