Fast Fusion of Medical Images Based on Bayesian Risk Minimization and Pixon Map

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 fulfil...

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Bibliographic Details
Published in:2009 International Conference on Computational Science and Engineering Vol. 2; pp. 1086 - 1091
Main Authors: Hongbo Zhou, Qiang Cheng, Zargham, M.
Format: Conference Proceeding
Language:English
Published: IEEE 01-08-2009
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Summary: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 multiresolution 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.
ISBN:9781424453344
1424453348
DOI:10.1109/CSE.2009.59