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Proceedings Paper

Novel medical image enhancement algorithms
Author(s): Sos Agaian; Stephen A. McClendon
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Paper Abstract

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Paper Details

Date Published: 8 February 2010
PDF: 12 pages
Proc. SPIE 7532, Image Processing: Algorithms and Systems VIII, 75320W (8 February 2010); doi: 10.1117/12.839003
Show Author Affiliations
Sos Agaian, The Univ. of Texas at San Antonio (United States)
Stephen A. McClendon, The Univ. of Texas at San Antonio (United States)


Published in SPIE Proceedings Vol. 7532:
Image Processing: Algorithms and Systems VIII
Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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