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KeyRes Run Length Matrix
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KeyRes Run Length Matrix is an advanced
features extraction and image processing software for scientific and industrial imaging applications based on Run Length Features.
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Reference:
[1] D. H. Xu, A. Kurani, J. D. Furst, & D. S. Raicu, "Run-length encoding for volumetric
texture", The 4th IASTED International Conference on Visualization, Imaging, and Image Processing - VIIP 2004, Marbella, Spain, September 6-8, 2004.
[2] F. Albregtsen, Statistical texture measures computed from gray level run-length matrices.
University of Oslo, 1995.
KeyRes Co-Occurrence Features v.1.32b
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KeyRes Co-Occurrence Features is an advanced
features extraction and image processing software for scientific and industrial imaging applications based on Haralick feature functions.
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| "Just a note to thank you for the excellent support we have received from your company.
We purchased KeyresCF software in 2005 and have used it extensively since that time."
T. A. McGilles, Vice President and General Manager, Image Fusion Inc.
"KeyRes Co-Occurrence Features Software has been one of the tremendous analysis software that I use on
a regular bases to extract information from image files".
Dr. A. Werner, Technical University of Munich, Germany.
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Reference:
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A. Zizzari,
et al., Detection of Tumor in Digital Images of the Brain. Proceedings
of the IASTED International Conference on Signal Processing, Pattern Recognition
and Applications SPPRA 2001, Rhodes, Greece, July 3-6, 2001, pp. 132-137.
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A. Zizzari,
Methods
on Tumor Recognition and Planning Target Prediction for the Radiotherapy
of Cancer. Shaker-Verlag, Aachen - Germany, 2004. (ISBN
3-8322-2562-5)
KeyRes RTOG/DICOM gui
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KeyRes
RTOG/DICOM gui is a special software
designed for handling and converting RTOG or DICOM image files, commonly
used in radiotherapy planning systems.
click here
for more information |
KeyRes DGE Algorithm
KeyRes DGE Algorithm is an advanced image
processing software for gray level enhancement in scientific and industrial imaging applications.
"DGE Algorithm
is the most spectacular improvement in image processing to be developed in the last two decades".
Prof. Andrew Harley, Editor in Chief - Microscopy Research and Technique.
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