Results 21 to 30 of about 3,529,155 (384)
Imaging in Interventional Radiology: 2043 and Beyond.
Radiology, 2023 Since its inception in the early 20th century, interventional radiology (IR) has evolved tremendously and is now a distinct clinical discipline with its own training pathway.
K. Brock +3 more
semanticscholar +1 more source
Applications and challenges of artificial intelligence in diagnostic and interventional radiology
Polish Journal of Radiology, 2022 Purpose Machine learning (ML) and deep learning (DL) can be utilized in radiology to help diagnosis and for predicting management and outcomes based on certain image findings.
J. Waller +6 more
semanticscholar +1 more source
JMIR Medical Education, 2022 BackgroundWith the move to virtual interviewing, residency websites are an important recruitment resource, introducing applicants to programs across the country and allowing for comparison. Recruitment is highly competitive from a
Katherine Jensen, Qi Yan, Mark G Davies
doaj +1 more source
Prime Time for Artificial Intelligence in Interventional Radiology
Cardiovascular and Interventional Radiology, 2022 Machine learning techniques, also known as artificial intelligence (AI), is about to dramatically change workflow and diagnostic capabilities in diagnostic radiology. The interest in AI in Interventional Radiology is rapidly gathering pace.
J. Seah, T. Boeken, M. Sapoval, G. Goh
semanticscholar +1 more source
Vascular and Interventional Radiology in Sudan
The Arab Journal of Interventional Radiology, 2021 There are only 4 interventional radiologists working in Sudan with many difficulties such as lack of resources and high cost of interventional equipments and procedures.
Alaaeldeen Mohammed Mohammed
doaj +1 more source
Deep Learning-Based Reconstruction of Interventional Tools from Four X-Ray Projections for Tomographic Interventional Guidance [PDF]
Eulig, E., et al. Deep learning-based reconstruction of
interventional tools and devices from four X-ray projections for tomographic
interventional guidance. Medical Physics. 2021; 48: 5837-5850, 2020 Image guidance for minimally invasive interventions is usually performed by acquiring fluoroscopic images using a C-arm system. However, the projective data provide only limited information about the spatial structure and position of interventional tools such as stents, guide wires or coils.
arxiv +1 more source
Interventional Radiology ex-machina: impact of Artificial Intelligence on practice
La radiologia medica, 2021 Artificial intelligence (AI) is a branch of Informatics that uses algorithms to tirelessly process data, understand its meaning and provide the desired outcome, continuously redefining its logic.
Martina Gurgitano +7 more
semanticscholar +1 more source
The Intrinsic Manifolds of Radiological Images and their Role in Deep Learning [PDF]
, 2022 The manifold hypothesis is a core mechanism behind the success of deep learning, so understanding the intrinsic manifold structure of image data is central to studying how neural networks learn from the data. Intrinsic dataset manifolds and their relationship to learning difficulty have recently begun to be studied for the common domain of natural ...
arxiv +1 more source
Simulator training for enhanced interventional radiology education. [PDF]
Sci RepTo address the challenges of staff shortages and the need to gain practical experience in interventional radiology by increasing attention in the medical curriculum, especially in combination with the opportunity to successfully gain hands-on experience,
Kronner N +9 more
europepmc +2 more sources
Interactive and Explainable Region-guided Radiology Report Generation [PDF]
2023 IEEE/CVF Conference on Computer Vision and Pattern
Recognition (CVPR), pp. 7433-7442, 2023 The automatic generation of radiology reports has the potential to assist radiologists in the time-consuming task of report writing. Existing methods generate the full report from image-level features, failing to explicitly focus on anatomical regions in the image.
arxiv +1 more source