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 language | English (US) |
|---|---|
| Title of host publication | 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010 |
| Pages | 21-24 |
| Number of pages | 4 |
| DOIs | |
| State | Published - 2010 |
| Event | 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010 - Cairo, Egypt Duration: Dec 16 2010 → Dec 18 2010 |
Other
| Other | 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010 |
|---|---|
| Country | Egypt |
| City | Cairo |
| Period | 12/16/10 → 12/18/10 |
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ASJC Scopus subject areas
- Biomedical Engineering
Cite this
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 proceeding › Conference contribution
}
TY - GEN
T1 - Improved segmentation technique to detect cardiac infarction in MRI C-SENC images
AU - Algohary, Ahmad O.
AU - El-Bialy, Ahmed M.
AU - Kandil, Ahmed H.
AU - Osman, Nael Fakhry
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=79952552107&partnerID=8YFLogxK
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U2 - 10.1109/CIBEC.2010.5716044
DO - 10.1109/CIBEC.2010.5716044
M3 - Conference contribution
SN - 9781424471706
SP - 21
EP - 24
BT - 2010 5th Cairo International Biomedical Engineering Conference, CIBEC 2010
ER -