A team of bioengineers at Rensselaer Polytechnic Institute (RPI), with funding from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), have developed an artificial intelligence ...

CT images of the chest and abdomen produced using low-dose AI reconstruction, low-dose conventional iterative reconstruction and normal-dose CT. (Courtesy: the Ge Wang group at RPI; the Mannudeep ...

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 ...

Machine learning has the potential to vastly advance medical imaging, particularly computerized tomography (CT) scanning, by reducing radiation exposure and improving image quality. Machine learning ...

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 ...

In the present paper, optimal quadrature formulas in the sense of Sard are constructed fornumerical integration of the integral ∫ a b e 2πiωx φ( x )dx with ω ∈ ℝ in the Sobolev space L 2 ( m ) [ a,b ] ...

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 ...

Comparison of routine spiral 4D CT and i4DCT imaging for regular and irregular breathing patterns. Left: normalized programmed breathing curves; green: beam-on periods; grey: beam-off periods; red: ...

The role of functional imaging is growing in clinical practice, where it is used to investigate the functional and physiological changes in the target. Unlike anatomical imaging, functional imaging is ...