Stainless steel is often used as a basis material for the antenna components.
Projection data were acquired with the high and low energy X-ray, respectively, to set up a basis material decomposition model.
Then the SNR of iodine in a basis material density image is (2) SN R Δ E (x, y ) ∝ μ L I (x, y ) − w I μ H I (x, y ) σ L 2 (x, y ) + (w I ) 2 σ H 2 (x, y ), where w I is weighting coefficient to produce the iodine density image, and subscript H indicates the high-kVp image.
In order for this to occur on a wide-spread basis, material properties of importance to design must be well understood.
Once a set of projections that covered the desired range were obtained for the respective lengths of basis material, a look-up table was generated.
Using an upstream plasma nitriding process, it is possible to produce a hardness gradient between the basis material and the coatings, thus ensuring a sufficient supporting effect for the coating.
Then the 2D projections of path lengths (d1, d2), which equaled (B1, B2), were used to reconstruct a 3D image of the basis material coefficient (b1, b2).
Next, we compute a noise mask for each basis material density image that is simply the difference between the original image, I m 1 (or I m 2), and its filtered version (i.e., the resultant image from the correlated anisotropic diffusion step described in Section 2.2) as follows: (9) N m 1 (x, y ) = I m 1 (x, y ) − ∂ I m 1 (x, y, t ) ∂ t, N m 2 (x, y ) = I m 2 (x, y ) − ∂ I m 2 (x, y, t ) ∂ t.
Noise reduction in dual-energy CT has been an active research area to obtain basis material density images of diagnostic quality.
Further, the crises as the basis material of this study were identified in a qualitative explorative way with a limited number of participants.
A key step of this method is to calculate the basis material coefficients calculation (b1 and b2) from the dual energy gray projections (g H and g L ).
