Sentence examples for material density images from inspiring English sources

The proposed algorithm can significantly reduce image noise present in basis material density images from dual-energy CT imaging, with minimized cross-contaminations compared to the ACNR algorithm.

Using pancreatic phase, CNR and SNR for PDA were obtained for DECT at monochromatic energies 50 through 80 keV, iodine material density images, and 120-kVp images.

For this reason, basis material density images are sometimes called "material density maps".

Both algorithms have significantly reduced the noises of basis material density images in all cases.

Since our algorithm performs diffusion in both basis material density images simultaneously, it is also more efficient than the original ACNR algorithms.

It is well known that the basis material density images suffer from much lower signal-to-noise ratio (SNR) than single-energy CT images.

Bonferroni correction was applied.Iodine material density image had significantly higher CNR and SNR for PDA than any monochromatic energy images (P < 0.0001) and the 120-kVp images.

Cross-contamination is very undesirable as it alters the original density values and introduces false anatomical or pathological information to the complimentary basis material density image.

This technique is based on the knowledge that image noises between the basis material density image pair are anticorrelated [ 1, 12, 17].

Taking advantage of this physical property, Kalender et al. has proposed to use a high-pass filtered version of the first basis material density image (e.g., water) to noise reduce the complimentary basis material density image (e.g., iodine) [ 12].

Having the identical geometry, the same reconstruction algorithm to reconstruct the single-energy CT images can therefore be applied to the first basis material projection data to obtain the corresponding basis material density image.