Two clustering techniques of myocardium using C-SENC images: A comparison with multi-stage clustering

Shereen M. El-Metwally; Nael F. Osman; Yasser M. Kadah; Ahmed S. Fahmy

doi:10.1109/ICCES.2007.4447051

Two clustering techniques of myocardium using C-SENC images: A comparison with multi-stage clustering

Shereen M. El-Metwally, Nael F. Osman, Yasser M. Kadah, Ahmed S. Fahmy

School of Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Simultaneous imaging of the myocardial function and viability is possible using the C-SENC acquisition technique previously proposed. The technique produces three gray-scale images that are combined to produce an image containing both function and viability information. In this paper, two techniques for combining the C-SENC images based on image clustering are proposed and compared. The first technique uses the pixel intensity in the 3 images to generate and cluster a 3D vector space. The second technique applies the clustering algorithm to the individual images then, the resulting clustered images are combined to produce a color image carrying the function and viability information. Finally, a comparison has been made with the multi-stage clustering technique previously proposed.

Original language	English (US)
Title of host publication	ICCES'07 - 2007 International Conference on Computer Engineering and Systems
Pages	215-219
Number of pages	5
DOIs	https://doi.org/10.1109/ICCES.2007.4447051
State	Published - Dec 1 2007
Event	2007 International Conference on Computer Engineering and Systems, ICCES'07 - Cairo, Egypt Duration: Nov 27 2007 → Nov 29 2007

Publication series

Name	ICCES'07 - 2007 International Conference on Computer Engineering and Systems

Other

Other	2007 International Conference on Computer Engineering and Systems, ICCES'07
Country	Egypt
City	Cairo
Period	11/27/07 → 11/29/07

ASJC Scopus subject areas

Computational Mechanics
Control and Systems Engineering

Access to Document

10.1109/ICCES.2007.4447051

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El-Metwally, S. M., Osman, N. F., Kadah, Y. M., & Fahmy, A. S. (2007). Two clustering techniques of myocardium using C-SENC images: A comparison with multi-stage clustering. In ICCES'07 - 2007 International Conference on Computer Engineering and Systems (pp. 215-219). [4447051] (ICCES'07 - 2007 International Conference on Computer Engineering and Systems). https://doi.org/10.1109/ICCES.2007.4447051

Two clustering techniques of myocardium using C-SENC images : A comparison with multi-stage clustering. / El-Metwally, Shereen M.; Osman, Nael F.; Kadah, Yasser M.; Fahmy, Ahmed S.

ICCES'07 - 2007 International Conference on Computer Engineering and Systems. 2007. p. 215-219 4447051 (ICCES'07 - 2007 International Conference on Computer Engineering and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

El-Metwally, SM, Osman, NF, Kadah, YM & Fahmy, AS 2007, Two clustering techniques of myocardium using C-SENC images: A comparison with multi-stage clustering. in ICCES'07 - 2007 International Conference on Computer Engineering and Systems., 4447051, ICCES'07 - 2007 International Conference on Computer Engineering and Systems, pp. 215-219, 2007 International Conference on Computer Engineering and Systems, ICCES'07, Cairo, Egypt, 11/27/07. https://doi.org/10.1109/ICCES.2007.4447051

El-Metwally SM, Osman NF, Kadah YM, Fahmy AS. Two clustering techniques of myocardium using C-SENC images: A comparison with multi-stage clustering. In ICCES'07 - 2007 International Conference on Computer Engineering and Systems. 2007. p. 215-219. 4447051. (ICCES'07 - 2007 International Conference on Computer Engineering and Systems). https://doi.org/10.1109/ICCES.2007.4447051

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abstract = "Simultaneous imaging of the myocardial function and viability is possible using the C-SENC acquisition technique previously proposed. The technique produces three gray-scale images that are combined to produce an image containing both function and viability information. In this paper, two techniques for combining the C-SENC images based on image clustering are proposed and compared. The first technique uses the pixel intensity in the 3 images to generate and cluster a 3D vector space. The second technique applies the clustering algorithm to the individual images then, the resulting clustered images are combined to produce a color image carrying the function and viability information. Finally, a comparison has been made with the multi-stage clustering technique previously proposed.",

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