Computed tomography (CT) has long been a cornerstone in medical diagnostics and materials science, enabling the non-invasive visualisation of internal structures. Recent decades have witnessed a shift ...
FedM2CT consists of 3 modules, i.e., task-specific iRadonMAP (TS-iRadonMAP), condition-prompted mutual learning (CPML), and federated metadata learning (FMDL). TS-iRadonMAP performs the local CT image ...
A machine learning model produced low-dose CT images with greater speed and accuracy than previous attempts to use less radiation in CT imaging, according to a study published this week in Nature ...
Aug. 16, 2022 — Oak Ridge National Laboratory has announced that a multidisciplinary team of researchers from ORNL and Purdue University won the Truth CT Reconstruction Grand Challenge, which was ...
Researchers at Fudan University are developing a reconstruction algorithm that enables quantitative bone imaging using ultrasonic computed tomography. (Courtesy: Dean Ta) Osteoporosis is a bone ...
TUSTIN, Calif.--(BUSINESS WIRE)--Bringing the power of artificial intelligence (AI) to molecular imaging, Advanced intelligent Clear-IQ Engine (AiCE), Canon Medical Systems USA Inc.’s Deep Learning ...
Tomographic Particle Image Velocimetry (Tomo-PIV) is a 3D particle image velocimetry technology combined with computed tomography (CT), which can realize full-field quantitative measurement of spatial ...
X-ray tomography is a powerful tool that enables scientists and engineers to peer inside of objects in 3D, including computer chips and advanced battery materials, without performing anything invasive ...