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Proceedings Paper

Resolution enhancement for x-ray images
Author(s): Hongquan Zuo; Jun Zhang
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Paper Abstract

X-ray machines are widely used for medical imaging and their cost is highly dependent on their image resolution. Due to economic reasons, lower-resolution (lower-res) machines still have a lot of customers, especially in developing economies. Software based resolution enhancement can potentially enhance the capabilities of the lower-res machines without significantly increasing their cost hence, is highly desirable. In this work, we developed an algorithm for X-ray image resolution enhancement. In this algorithm, the fractal idea and cross-resolution patch matching are used to identify low-res patches that can be used as samples for high-res patch/pixel estimation. These samples are then used to generate a prior distribution and used in a Bayesian MAP (maximum a posteriori) optimization to produce the high-res image estimate. The efficacy of our algorithm is demonstrated by experimental results.

Paper Details

Date Published: 24 February 2017
PDF: 7 pages
Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101331L (24 February 2017); doi: 10.1117/12.2250666
Show Author Affiliations
Hongquan Zuo, Univ. of Wisconsin-Milwaukee (United States)
Jun Zhang, Univ. of Wisconsin-Milwaukee (United States)


Published in SPIE Proceedings Vol. 10133:
Medical Imaging 2017: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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