Minimum data image reconstruction algorithms with shift-invariant filtering for helical, cone-beam CT.
We derive accurate and efficient reconstruction algorithms for helical, cone-beam CT that employ shift-invariant filtering. Specifically, a new backprojection-filtration algorithm is developed, and a minimum data filtered-backprojection algorithm is derived. These reconstruction algorithms with shift-invariant filtering can accept data with transverse truncation, and hence allow for minimum data image reconstruction.
Sidky
Emil Y
EY
Department of Radiology MC-2026, University of Chicago, IL 60637, USA.
Zou
Yu
Y
Pan
Xiaochuan
X
D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009716:Numerical Analysis, Computer-Assisted; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D036542:Tomography, Spiral Computed / Q000379:methods*