Improved segmentation technique to detect cardiac infarction in MRI C-SENC images

Ahmad O. Algohary, Ahmed M. El-Bialy, Ahmed H. Kandil, Nael Fakhry Osman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Composite Strain Encoding (C-SENC) is a new MRI technique that acquires cardiac functional and viability images simultaneously. It combines the use of Delayed Enhancement (DE) imaging to identify the infracted (dead) tissue inside the heart muscle and the ability to image myocardial deformation from the Strain Encoding (SENC) imaging technique. In this work, a new multi-stage technique is proposed to objectively identify infarcted heart tissues in the functional and viability images provided by C-SENC MRI. The proposed technique is based on sequential application of Bayes classifier, Otsu's thresholding, morphological opening, radial sweep boundary tracing and the fuzzy C-means (FCM) clustering algorithm. This technique is tested on images of eleven patients suffering myocardial infarction (MI). The resulting clustered images are compared with those marked up by expert cardiologists who assisted in validating results coming from the proposed technique. Infarcted myocardium is correctly identified using the proposed technique with high levels of accuracy and precision.

Original languageEnglish (US)
Title of host publication2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010
Pages21-24
Number of pages4
DOIs
StatePublished - 2010
Event2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010 - Cairo, Egypt
Duration: Dec 16 2010Dec 18 2010

Other

Other2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010
CountryEgypt
CityCairo
Period12/16/1012/18/10

Fingerprint

Magnetic resonance imaging
Composite materials
Tissue
Imaging techniques
Clustering algorithms
Muscle
Classifiers

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Algohary, A. O., El-Bialy, A. M., Kandil, A. H., & Osman, N. F. (2010). Improved segmentation technique to detect cardiac infarction in MRI C-SENC images. In 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010 (pp. 21-24). [5716044] https://doi.org/10.1109/CIBEC.2010.5716044

Improved segmentation technique to detect cardiac infarction in MRI C-SENC images. / Algohary, Ahmad O.; El-Bialy, Ahmed M.; Kandil, Ahmed H.; Osman, Nael Fakhry.

2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010. 2010. p. 21-24 5716044.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Algohary, AO, El-Bialy, AM, Kandil, AH & Osman, NF 2010, Improved segmentation technique to detect cardiac infarction in MRI C-SENC images. in 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010., 5716044, pp. 21-24, 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010, Cairo, Egypt, 12/16/10. https://doi.org/10.1109/CIBEC.2010.5716044
Algohary AO, El-Bialy AM, Kandil AH, Osman NF. Improved segmentation technique to detect cardiac infarction in MRI C-SENC images. In 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010. 2010. p. 21-24. 5716044 https://doi.org/10.1109/CIBEC.2010.5716044
Algohary, Ahmad O. ; El-Bialy, Ahmed M. ; Kandil, Ahmed H. ; Osman, Nael Fakhry. / Improved segmentation technique to detect cardiac infarction in MRI C-SENC images. 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010. 2010. pp. 21-24
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