Automated cardiac-tissue identification in composite strain-encoded (C-SECN) images using fuzzy K-means and bayesian classifier

Abdallah G. Motaal, Neamat El-Gayar, Nael F. Osman

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

3 Citations (Scopus)

Abstract

Composite Strain Encoding (C-SENC) is an MRI acquisition technique for simultaneous acquisition of cardiac tissue viability and contractility images. It combines the use of black-blood delayed-enhancement imaging to identify the infracted (dead) tissue inside the heart wall muscle and the ability to image myocardial deformation (MI) from the strain-encoding (SENC) imaging technique. In this work, we propose an automatic image processing technique to identify the different heart tissues. This provides physicians with a better clinical decision-making tool in patients with myocardial infarction. The technique is based on using Bayesian classifier to identify the background regions in the C-SENC images, and fuzzy clustering technique to identify the different types of the heart tissues. The proposed method is tested using numerical simulations of the heart C-SENC images with MI and real images of patients. The results show that the proposed technique is able to identify the different components of the image with a high accuracy.

Original languageEnglish
Title of host publication2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE)
PublisherIEEE
ISBN (Print)9781424447121
DOIs
Publication statusPublished - 23 Jul 2010
Event4th International Conference on Bioinformatics and Biomedical Engineering 2010 - Chengdu, China
Duration: 18 Jun 201020 Jun 2010

Conference

Conference4th International Conference on Bioinformatics and Biomedical Engineering 2010
Abbreviated titleiCBBE 2010
CountryChina
CityChengdu
Period18/06/1020/06/10

Keywords

  • Bayesian classifier
  • Cardiac magnetic resonance
  • Composite senc
  • Delayed enhancement
  • Fuzzy k-means clustering
  • SENC
  • Strain encoding

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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  • Cite this

    Motaal, A. G., El-Gayar, N., & Osman, N. F. (2010). Automated cardiac-tissue identification in composite strain-encoded (C-SECN) images using fuzzy K-means and bayesian classifier. In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE) [5517766] IEEE. https://doi.org/10.1109/ICBBE.2010.5517766