title: Minimum data image reconstruction algorithms with shift-invariant filtering for helical, cone-beam CT.
abstract: 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.
authors.affiliation: Department of Radiology MC-2026, University of Chicago, IL 60637, USA.
authors.forename: Emil Y
authors.initials: EY
authors.lastname: Sidky
authors.forename: Yu
authors.initials: Y
authors.lastname: Zou
authors.forename: Xiaochuan
authors.initials: X
authors.lastname: Pan
mesh_terms: 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*