Fast Fusion of Medical Images Based on Bayesian Risk Minimization and Pixon Map
Document Type
Conference Paper
Publication Date
8-2009
Publication Source
International Conference on Computational Science and Engineering
Abstract
Fast fusion of multiple registered out-of-focus images is of great interest in medical imaging; for example, the thoracic cavity is always too bumpy to be focused on all parts at one shot even when we can omit the unavoidable hardware vibrations. Previous proposed methods in this field cannot fulfill the real-time requirement in our multiple camera medical imaging setting. In this paper, we propose a multi-resolution Bayesian risk minimization based method to fuse these chest cavity images. The validity and efficiency of our method are verified by our experiments on both out-of-focus medical images and regional motion blurred images. By choosing special kernel functions for the Pixon map and adopting uniform distribution as the prior probability, our method can be applied to the real-time medical imaging situations such as surgical operation monitoring.
Inclusive pages
1086-1091
ISBN/ISSN
9781424453344
Copyright
Copyright © 2009, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher
Institute of Electrical and Electronics Engineers
Peer Reviewed
yes
eCommons Citation
Zhou, Hongbo; Cheng, Qiang; and Zargham, Mehdi, "Fast Fusion of Medical Images Based on Bayesian Risk Minimization and Pixon Map" (2009). Computer Science Faculty Publications. 157.
https://ecommons.udayton.edu/cps_fac_pub/157
COinS
Comments
Permission documentation on file.