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Proceedings Paper

Entropy fractal analysis of medical images using ROSETA
Author(s): Holger M. Jaenisch; Marvin P. Carroll; Jim Scoggins; James W. Handley
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Paper Abstract

The use of fractal statistics for characterizing and synthesizing medical imagery has in recent time been demonstrated as feasible. Traditionally, global fractal dimensions based on morphological coverings were used to quantify the texture of sampled data sets. This texture could be used to describe the second order statistics in 2D Magnetic Resonance Imaging, or microscopic images. With the realization of the benefits of fractal analysis has come a need for faster and more efficient computational algorithms. ROSETA (Range Over Standard Deviation, Experimental Trend Analysis) is an algorithm which yields substantial computational performance improvements by calculating entropy-based fractal statistics instead of morphological geometric statistics. ROSETA may be used as a robust general purpose analytical tool and several examples of its implementation are described. A simple variation of this algorithm is also presented which facilitates manual calculation using a calculator. This simple fixed point calculation may be used to analyze blood pressure, temperature, and heart rates as select discrete time samples with very few total points.

Paper Details

Date Published: 26 May 1994
PDF: 10 pages
Proc. SPIE 2132, Clinical Applications of Modern Imaging Technology II, (26 May 1994); doi: 10.1117/12.176574
Show Author Affiliations
Holger M. Jaenisch, Tec-Masters, Inc. (United States)
Marvin P. Carroll, Tec-Masters, Inc. (United States)
Jim Scoggins, Tec-Masters, Inc. (United States)
James W. Handley, Tec-Masters, Inc. (United States)


Published in SPIE Proceedings Vol. 2132:
Clinical Applications of Modern Imaging Technology II
Leonard J. Cerullo; Kenneth S. Heiferman; Hong Liu; Halina Podbielska; Abund Ottokar Wist; Lucia J. Zamorano, Editor(s)

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