Abstract
The low spatial resolution of Positron Emission Tomography imaging (PET) is due to the width of detector and some physical parameters (such as scattering fraction, counting statistics, positron range and patient’s motion). To overcome this problem and improve the resolution of PET image, a high effective sub-pixel registration algorithm based on Keren’s method is proposed, and a new iteration algorithm of registration is introduced to improve the registration accuracy. Compared with Keren’s method, this method can improve the registration accuracy highly. This new registration algorithm is applied into super-resolution PET imaging. What’s more, this new super-resolution approach will be demonstrated in this paper.
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Yan, P.M., Yang, M., Huang, H., Li, J.F. (2012). An Improved Approach to Super Resolution Based on PET Imaging. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34500-5_11
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DOI: https://doi.org/10.1007/978-3-642-34500-5_11
Publisher Name: Springer, Berlin, Heidelberg
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