Numerical Optimization of the Filter Function Used in the Convolution Filtered Back Projection Algorithm for Computed Tomography |
Common terms and phrases
actual aliasing amount analysis application approximate arbitrary artefact average calculation chosen coefficients complete computation Computed Tomography considered constraint convolution filtered back decrease definition density dependence describes determine developed difficult distance edge effect equal equation error evaluating Examination fact factor figure filter function filtered back projection follows Fourier transform gives image quality important independent iterative least linear combination linear interpolation Logan major matrix measure of image method minimized needed noise noise and resolution Note numerical object observation obtained optimization algorithm optimum performed phantom photon noise pixels possible practical presented problem produce quadratic function r₁ raysums reconstructed image reduces refer remains resolution response scanner Shepp and Logan's shows simply single solved square step functions Substituting summation thesis unit University values zero order interpolation