DocumentCode :
1084308
Title :
General reconstruction theory for multislice X-ray computed tomography with a gantry tilt
Author :
Noo, Frédéric ; Defrise, Michel ; Kudo, Hiroyuki
Author_Institution :
Dept. of Radiol., Utah Univ., Salt Lake City, UT, USA
Volume :
23
Issue :
9
fYear :
2004
Firstpage :
1109
Lastpage :
1116
Abstract :
This paper discusses image reconstruction with a tilted gantry in multislice computed tomography (CT) with helical (spiral) data acquisition. The reconstruction problem with gantry tilt is shown to be transformable into the problem of reconstructing a virtual object from multislice CT data with no gantry tilt, for which various algorithms exist in the literature. The virtual object is related to the real object by a simple affine transformation that transforms the tilted helical trajectory of the X-ray source into a nontilted helix, and the real object can be computed from the virtual object using one-dimensional interpolation. However, the interpolation may be skipped since the reconstruction of the virtual object on a Cartesian grid provides directly nondistorted images of the real object on slices parallel to the tilted plane of the gantry. The theory is first presented without any specification of the detector geometry, then applied to the curved detector geometry of third-generation CT scanners with the use of Katsevich´s formula for example. Results from computer-simulated data of the FORBILD thorax phantom are given in support of the theory.
Keywords :
computerised tomography; data acquisition; image reconstruction; medical image processing; phantoms; Cartesian grid; FORBILD thorax phantom; Katsevich formula; affine transformation; curved detector geometry; directly nondistorted images; gantry tilt; general reconstruction theory; helical data acquisition; image reconstruction; multislice X-ray computed tomography; third-generation CT scanners; Computed tomography; Data acquisition; Detectors; Geometry; Image reconstruction; Imaging phantoms; Interpolation; Spirals; Thorax; X-ray imaging; Algorithms; Anatomy, Cross-Sectional; Humans; Models, Biological; Models, Statistical; Phantoms, Imaging; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Radiography, Thoracic; Reproducibility of Results; Sensitivity and Specificity; Tomography, Spiral Computed;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2004.829337
Filename :
1327690
Link To Document :
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