AIMC Journal:
European radiology

Showing 281 to 290 of 621 articles

Automated segmentation of craniopharyngioma on MR images using U-Net-based deep convolutional neural network.

European radiology Nov 18, 2022
OBJECTIVES: To develop a U-Net-based deep learning model for automated segmentation of craniopharyngioma.
Pituitary Neoplasms Neural Networks, Computer Image Processing, Computer-Assisted Craniopharyngioma Humans Magnetic Resonance Imaging Deep Learning
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Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation.

European radiology Nov 18, 2022
OBJECTIVE: To investigate the utility of an automatic deep learning (DL) method for segmentation of T2 maps in patients with idiopathic inflammatory myopathy (IIM) against healthy controls, and also the association of quantitative T2 values in patien...
Animals Muscle, Skeletal Myositis Lung Diseases, Interstitial Deep Learning Inflammation
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MR-self Noise2Noise: self-supervised deep learning-based image quality improvement of submillimeter resolution 3D MR images.

European radiology Nov 15, 2022
OBJECTIVES: The study aimed to develop a deep neural network (DNN)-based noise reduction and image quality improvement by only using routine clinical scans and evaluate its performance in 3D high-resolution MRI.
Humans Quality Improvement Retrospective Studies Imaging, Three-Dimensional Image Processing, Computer-Assisted Deep Learning Magnetic Resonance Imaging
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Musculoskeletal radiologist-level performance by using deep learning for detection of scaphoid fractures on conventional multi-view radiographs of hand and wrist.

European radiology Nov 15, 2022
OBJECTIVES: To assess how an artificial intelligence (AI) algorithm performs against five experienced musculoskeletal radiologists in diagnosing scaphoid fractures and whether it aids their diagnosis on conventional multi-view radiographs.
Radiologists Wrist Wrist Injuries Scaphoid Bone Retrospective Studies Deep Learning Fractures, Bone Humans Artificial Intelligence
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Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI.

European radiology Nov 12, 2022
OBJECTIVES: Prostate volume (PV) in combination with prostate specific antigen (PSA) yields PSA density which is an increasingly important biomarker. Calculating PV from MRI is a time-consuming, radiologist-dependent task. The aim of this study was t...
Humans Prostate-Specific Antigen Retrospective Studies Prostate Sensitivity and Specificity Magnetic Resonance Imaging Male Algorithms Observer Variation Organ Size Radiologists Deep Learning Prostatic Neoplasms
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Rapid 3D breath-hold MR cholangiopancreatography using deep learning-constrained compressed sensing reconstruction.

European radiology Nov 10, 2022
OBJECTIVES: To compare the image quality of three-dimensional breath-hold magnetic resonance cholangiopancreatography with deep learning-based compressed sensing reconstruction (3D DL-CS-MRCP) to those of 3D breath-hold MRCP with compressed sensing (...
Pancreatic Diseases Pancreatic Ducts Cholangiopancreatography, Magnetic Resonance Deep Learning Imaging, Three-Dimensional Humans
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Deep learning-based harmonization of CT reconstruction kernels towards improved clinical task performance.

European radiology Nov 10, 2022
OBJECTIVES: To develop a deep learning-based harmonization framework, assessing whether it can improve performance of radiomics models given different kernels in different clinical tasks and additionally generalize to mitigate the effects of new/unob...
Reproducibility of Results Deep Learning Lung Neoplasms Humans Tomography, X-Ray Computed Tuberculosis, Pulmonary Task Performance and Analysis
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CT image quality evaluation in the age of deep learning: trade-off between functionality and fidelity.

European radiology Nov 9, 2022
OBJECTIVE: To quantitatively compare DLIR and ASiR-V with realistic anatomical images.
Deep Learning Image Processing, Computer-Assisted Humans Radiation Dosage Algorithms Radiographic Image Interpretation, Computer-Assisted Radionuclide Imaging Tomography, X-Ray Computed
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Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?

European radiology Nov 3, 2022
OBJECTIVES: To compare the image quality and hepatic metastasis detection of low-dose deep learning image reconstruction (DLIR) with full-dose filtered back projection (FBP)/iterative reconstruction (IR).
Prospective Studies Tomography, X-Ray Computed Deep Learning Humans Algorithms Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Phantoms, Imaging Liver Neoplasms Image Processing, Computer-Assisted
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SAM-X: sorting algorithm for musculoskeletal x-ray radiography.

European radiology Oct 29, 2022
OBJECTIVE: To develop a two-phased deep learning sorting algorithm for post-X-ray image acquisition in order to facilitate large musculoskeletal image datasets according to their anatomical entity.
Musculoskeletal Diseases Retrospective Studies Humans X-Rays Deep Learning Algorithms Radiography
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