Authors:
Tomohiro Aoyagi
and
Kouichi Ohtsubo
Affiliation:
Faculty of Information Science and Arts, Toyo University, 2100 Kujirai, Saitama, Japan
Keyword(s):
X-ray CT, PET, Image Reconstruction, ISRA, Steepest Descent.
Abstract:
In medical imaging modality, such as X-ray computerized tomography (CT), positron emission tomography (PET) and single photon emission computed tomography (SPECT), image reconstruction from projection is to produce an image of a two-dimensional object from estimates of its line integrals along a finite number of lines of known locations. The method of tomographic image reconstruction from projection can be formulated with the Fredholm integral equation of the first kind, mathematically. It is necessary to solve the equation. But it is difficult in general to seek the strict solution. By discretizing the image reconstruction problem, we applied the image space reconstruction algorithm (ISRA) to the problem and evaluated the image quality. We computed the normalized mean square error (NMSE) in reconstructed image. We have shown that the error decreases with increasing the number of detectors, views and iterations. In addition, the effect of the relaxation parameter, the weighting facto
r and the noise to the reconstructed image are analysed.
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