AIMC Topic: Magnetic Resonance Imaging
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AIFNet: Automatic vascular function estimation for perfusion analysis using deep learning.
Medical image analysis
Aug 6, 2021
Perfusion imaging is crucial in acute ischemic stroke for quantifying the salvageable penumbra and irreversibly damaged core lesions. As such, it helps clinicians to decide on the optimal reperfusion treatment. In perfusion CT imaging, deconvolution ...
Uncertainty estimation and explainability in deep learning-based age estimation of the human brain: Results from the German National Cohort MRI study.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 6, 2021
Brain ageing is a complex neurobiological process associated with morphological changes that can be assessed on MRI scans. Recently, Deep learning (DL)-based approaches have been proposed for the prediction of chronological brain age from MR images y...
Association of Machine Learning-Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis.
Arthritis & rheumatology (Hoboken, N.J.)
Aug 6, 2021
OBJECTIVE: The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this study to develop an equation to predict the medial tibiofemoral contact force (MCF) peak during walking ...
Artificial Intelligence-Based Data Corrections for Attenuation and Scatter in Position Emission Tomography and Single-Photon Emission Computed Tomography.
PET clinics
Aug 5, 2021
Recent developments in artificial intelligence (AI) technology have enabled new developments that can improve attenuation and scatter correction in PET and single-photon emission computed tomography (SPECT). These technologies will enable the use of ...
Detection and PI-RADS classification of focal lesions in prostate MRI: Performance comparison between a deep learning-based algorithm (DLA) and radiologists with various levels of experience.
European journal of radiology
Aug 5, 2021
PURPOSE: To compare the performance of lesion detection and Prostate Imaging-Reporting and Data System (PI-RADS) classification between a deep learning-based algorithm (DLA), clinical reports and radiologists with different levels of experience in pr...
A Novel Method for Differential Prognosis of Brain Degenerative Diseases Using Radiomics-Based Textural Analysis and Ensemble Learning Classifiers.
Computational and mathematical methods in medicine
Aug 5, 2021
We propose a novel approach to develop a computer-aided decision support system for radiologists to help them classify brain degeneration process as physiological or pathological, aiding in early prognosis of brain degenerative diseases. Our approach...
Automatic segmentation of the temporomandibular joint disc on magnetic resonance images using a deep learning technique.
Dento maxillo facial radiology
Aug 4, 2021
OBJECTIVES: The aims of the present study were to construct a deep learning model for automatic segmentation of the temporomandibular joint (TMJ) disc on magnetic resonance (MR) images, and to evaluate the performances using the internal and external...
Assessment of MRI technologists in acceptance and willingness to integrate artificial intelligence into practice.
Radiography (London, England : 1995)
Aug 4, 2021
INTRODUCTION: The integration of AI in medical imaging has tremendous exponential growth, especially in image production, image processing and image interpretation. It is expected that radiographers working across all imaging modalities have adequate...
Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images.
Computer methods and programs in biomedicine
Aug 4, 2021
BACKGROUND: After the treatment of the patients with malignant lymphoma, there may persist lesions that must be labeled either as evolutive lymphoma requiring new treatments or as residual masses. We present in this work, a machine learning-based com...
Residual dense network for medical magnetic resonance images super-resolution.
Computer methods and programs in biomedicine
Aug 4, 2021
BACKGROUND AND OBJECTIVE: High-resolution magnetic resonance images (MRI) help experts to localize lesions and diagnose diseases, but it is difficult to obtain high-resolution MRI. Furthermore, image super-resolution technology based on deep learning...
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