AIMC Journal:
European radiology

Showing 411 to 420 of 621 articles

Differential diagnosis of benign and malignant vertebral fracture on CT using deep learning.

European radiology May 16, 2021
OBJECTIVES: To evaluate the performance of deep learning using ResNet50 in differentiation of benign and malignant vertebral fracture on CT.
Diagnosis, Differential Humans Spinal Fractures Retrospective Studies Tomography, X-Ray Computed Deep Learning
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ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging.

European radiology May 15, 2021
Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis. AI systems should ensure that the main benefits of biopsy avoidance are delivered while maintaining consistent hi...
Humans Artificial Intelligence Prostatic Neoplasms Image-Guided Biopsy Male Magnetic Resonance Imaging
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Detection of liver cirrhosis in standard T2-weighted MRI using deep transfer learning.

European radiology May 11, 2021
OBJECTIVES: To investigate the diagnostic performance of deep transfer learning (DTL) to detect liver cirrhosis from clinical MRI.
Retrospective Studies Female Male Image Processing, Computer-Assisted Neural Networks, Computer Machine Learning Humans Liver Cirrhosis Magnetic Resonance Imaging
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An international survey on AI in radiology in 1041 radiologists and radiology residents part 2: expectations, hurdles to implementation, and education.

European radiology May 11, 2021
OBJECTIVES: Currently, hurdles to implementation of artificial intelligence (AI) in radiology are a much-debated topic but have not been investigated in the community at large. Also, controversy exists if and to what extent AI should be incorporated ...
Surveys and Questionnaires Radiology Humans Radiologists Artificial Intelligence Motivation
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Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-weighted FS sequence.

European radiology May 7, 2021
OBJECTIVE: To compare the image quality of an accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction (DL HASTE-FS) with conventional T2-weighted FS sequence (conventional T2 FS) at 1.5 T...
Magnetic Resonance Imaging Liver Artifacts Deep Learning Image Processing, Computer-Assisted Humans
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Artificial intelligence to predict task activation from resting state fMRI.

European radiology May 7, 2021
Magnetic Resonance Imaging Brain Mapping Artificial Intelligence Brain Rest Humans
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Proposing a deep learning-based method for improving the diagnostic certainty of pulmonary nodules in CT scan of chest.

European radiology May 6, 2021
OBJECTIVE: To compare the performance of a deep learning (DL)-based method for diagnosing pulmonary nodules compared with radiologists' diagnostic approach in computed tomography (CT) of the chest.
Tomography, X-Ray Computed Deep Learning Humans Solitary Pulmonary Nodule Lung Neoplasms Multiple Pulmonary Nodules
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Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study.

European radiology May 4, 2021
OBJECTIVES: Digital breast tomosynthesis (DBT) increases sensitivity of mammography and is increasingly implemented in breast cancer screening. However, the large volume of images increases the risk of reading errors and reading time. This study aims...
Mammography Breast Artificial Intelligence Humans Female Breast Neoplasms Early Detection of Cancer
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Automatic prediction of left cardiac chamber enlargement from chest radiographs using convolutional neural network.

European radiology May 3, 2021
OBJECTIVE: To develop deep learning-based cardiac chamber enlargement-detection algorithms for left atrial (DLCE-LAE) and ventricular enlargement (DLCE-LVE), on chest radiographs METHODS: For training and internal validation of DLCE-LAE and -LVE, 5,0...
Humans Neural Networks, Computer Radiography Algorithms Radiography, Thoracic Deep Learning
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Translation of predictive modeling and AI into clinics: a question of trust.

European radiology Apr 25, 2021
Artificial Intelligence Humans Trust
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