DocumentCode :
2193703
Title :
A local iterative reconstruction algorithm for planar integral data
Author :
Zeng, Gengsheng L. ; Gagnon, Daniel ; Natterer, Frank ; Wang, Wenli ; Wrinkler, Marc ; Hawkins, William
Author_Institution :
Med. Imaging Res. Lab., Utah Univ., Salt Lake City, UT, USA
Volume :
2
fYear :
2002
fDate :
10-16 Nov. 2002
Firstpage :
751
Abstract :
In this paper we develop an iterative algorithm for a set of parallel weighted or unweighted planar integrals of an object. The object is relative large and the entire object is not sufficiently measured, and the projections are truncated due to a small detector size. However, a small region-of-interest (ROI) is sufficiently measured. It is known that the Radon inversion formula is able to exactly reconstruct the ROI with truncated parallel unweighted planar integrals (i.e., the three-dimensional Radon transform). This local tomographic property is not found for line-integral measurements. The local tomography is usually not available when using iterative reconstruction methods because the forward-projection of the entire image of the object is impossible. This paper investigates an iterative algorithm that is able to accurately reconstruct the ROI using truncated planar integral data.
Keywords :
image reconstruction; iterative methods; medical image processing; single photon emission computed tomography; Radon inversion formula; SPECT; local iterative reconstruction algorithm; local tomographic property; parallel weighted integrals; planar integral data; single photon emission computed tomography; small region-of-interest; unweighted planar integrals; Detectors; Extraterrestrial measurements; Image reconstruction; Iterative algorithms; Kernel; Object detection; Reconstruction algorithms; Strips; Tomography; Transmission line matrix methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nuclear Science Symposium Conference Record, 2002 IEEE
Print_ISBN :
0-7803-7636-6
Type :
conf
DOI :
10.1109/NSSMIC.2002.1239432
Filename :
1239432
Link To Document :
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