Name
Abstract | ||
|---|---|---|
ABSTRACT Toresolve fine details, or to accurately segment tumors from background activities, it is desired that the reconstruction image of the SPECT may preserve the edges and achieve high resolution. In this paper, we develop a blind deblurring reconstruction technique estimate of both the actual image and the PSF of the system, and enhance the performance,of iterative reconstruction using this technique. Ablurred,SPECT reconstruction can be viewed ,as the convolution of a low-pass PSF with the actual image, where both the PSF and the actual image are unknown,in practice. The PSF of a SPECT system is determined by the combined effect of several factors, which include the gamma camera PSF, the scattering, and pinhole PSF for pinhole SPECT systems, and therefore is hard to be determined analytically. Inspired by the blind deconvolution algorithm[1], we formulate a blind deblurring reconstruction algorithm, which also consists of two iterative update sequences, which are corresponded for the PSF and the SPECT reconstruction, respectively. In the phantom study, the algorithm reduces image blurring and preserves the edges without introducing extra artifacts. The localized measurement ,shows ,that the performance,of reconstruction image ,improved ,by up ,to 50%. In experimental studies, the contrast and quality of reconstruction is substantially improved. Therefore, algorithm,shows ,promising ,in tumor ,localization and quantification. Index Terms— SPECT, deblurring, iterative reconstruction |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1155/2009/718157 | International Journal of Biomedical Imaging |
Keywords | Field | DocType |
reconstruction image,blind iterative reconstruction scheme,pet imaging,actual image,account system,high quality,experimental data,blind deblurring reconstruction technique,synthetic data study,experimental data study,proposed reconstruction technique,iterative methods,high resolution,indexing terms,attenuation,image restoration,physics,point spread function,blind deconvolution,detectors,cancer,measurement errors,low pass,iterative reconstruction,image reconstruction | Iterative reconstruction,Computer vision,Deblurring,Pattern recognition,Experimental data,Iterative method,Computer science,Synthetic data,Artificial intelligence,Image restoration,Point spread function,System model | Journal |
Volume | ISSN | Citations |
2009 | 1687-4188 | 1 |
PageRank | References | Authors |
0.41 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heng Li | 1 | 1 | 1.42 |
| feng qiao | 2 | 1 | 0.41 |
| Osama R. Mawlawi | 3 | 1 | 1.09 |
| Yibin Zheng | 4 | 38 | 15.13 |
| Ronald X. Zhu | 5 | 1 | 0.41 |