Search Tag: Deep Learning
2024 09 Apr
The evolution of computing power has revolutionized the field of medical imaging, particularly in the realm of computed tomography (CT). One of the significant milestones in this evolution has been the introduction of iterative reconstruction methods, aimed at reducing image noise and radiation dose in CT scans. Initially, these methods were combined...Read more
2024 09 Apr
The evolution of computing power has revolutionized the field of medical imaging, particularly in the realm of computed tomography (CT). One of the significant milestones in this evolution has been the introduction of iterative reconstruction methods, aimed at reducing image noise and radiation dose in CT scans. Initially, these methods were combined...Read more
2024 01 Feb
Research into the use of AI methods to enhance MRI scan acquisition, particularly in musculoskeletal radiology, has seen significant advancement since 2016. While initial studies show promise in improving image resolution and speeding up imaging processes, questions remain about the reliability of AI-generated images for routine clinical use. Establishing...Read more
2024 01 Feb
Research into the use of AI methods to enhance MRI scan acquisition, particularly in musculoskeletal radiology, has seen significant advancement since 2016. While initial studies show promise in improving image resolution and speeding up imaging processes, questions remain about the reliability of AI-generated images for routine clinical use. Establishing...Read more
2022 13 Jan
Fluid-attenuation inversion recovery (FLAIR) is a commonly-used sequence for estimating the age of an acute ischemic stroke. Timing information is essential for considering intravenous tissue plasminogen activator (tPA) to treat ischaemic stroke. One critical advantage synthetic FLAIR have over conventional FLAIR is its potential to reduce scan times in...Read more
2020 10 Feb
A new study published in the journal Radiology describes the feasibility of using a deep learning model to accurately assess radiographic features of hip osteoarthritis. The AI model's performance even rivalled the accuracy of trained radiologists , according to researchers. You might also like: White Paper...Read more
2017 07 Mar
Royal Philips and LabPON, the first clinical laboratory to transition to 100% histopathology digital diagnosis, has announced its plans to create a digital database of massive aggregated sets of annotated pathology images and big data utilizing Philips IntelliSite Pathology Solution 1 . The database will provide pathologists with a wealth of clinical...Read more