BACKGROUND: In magnetic resonance image (MRI)-guided radiotherapy (MRgRT), 2D rapid imaging is commonly used to track moving targets with high temporal frequency to minimize gating latency. However, anatomical motion is not constrained to 2D, and a p...
BACKGROUND: It is unclear regarding the association between metabolomic state/genetic risk score(GRS) and brain volumes and how much of variance of brain volumes is attributable to metabolomic state or GRS.
PURPOSE: To evaluate the effect of lower field strength on quantitative apparent-diffusion-coefficient (ADC) values, contrast of the T2-weighted MR images and the performance of an AI-based segmentation.
Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Dec 2, 2024
Magnetic resonance imaging (MRI) of the knee is the recommended diagnostic method before invasive arthroscopy surgery. Nevertheless, interpreting knee MRI scans is a time-consuming process that is vulnerable to inaccuracies and inconsistencies. We pr...
OBJECTIVE: To explore the performance of deep learning-based segmentation of infarcted lesions in the brain magnetic resonance imaging (MRI) of patients with acute ischemic stroke (AIS) and the recurrence prediction value of radiomics within 1 year a...
Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot. However, image quality is limited by a lower signal-to-n...
Medical image analysis poses significant challenges due to limited availability of clinical data, which is crucial for training accurate models. This limitation is further compounded by the specialized and labor-intensive nature of the data annotatio...
Analysis of functional connectivity networks (FCNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) has greatly advanced our understanding of brain diseases, including Alzheimer's disease (AD) and attention deficit hyperact...
Quantitative infarct estimation is crucial for diagnosis, treatment and prognosis in acute ischemic stroke (AIS) patients. As the early changes of ischemic tissue are subtle and easily confounded by normal brain tissue, it remains a very challenging ...
IEEE transactions on neural networks and learning systems
Dec 2, 2024
Transfer learning has attracted considerable attention in medical image analysis because of the limited number of annotated 3-D medical datasets available for training data-driven deep learning models in the real world. We propose Medical Transformer...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.