Faculty Collaboration Database

Identification of different heart tissues from MRI C-SENC images using an unsupervised multi-stage fuzzy clustering technique. J Magn Reson Imaging 2008 Aug;28(2):519-26

Date

07/31/2008

Pubmed ID

18666217

Pubmed Central ID

PMC2567102

DOI

10.1002/jmri.21452

Scopus ID

2-s2.0-49049118452 (requires institutional sign-in at Scopus site)   14 Citations

Abstract

PURPOSE: To objectively characterize different heart tissues from functional and viability images provided by composite-strain-encoding (C-SENC) MRI.

MATERIALS AND METHODS: C-SENC is a new MRI technique for simultaneously acquiring cardiac functional and viability images. In this work, an unsupervised multi-stage fuzzy clustering method is proposed to identify different heart tissues in the C-SENC images. The method is based on sequential application of the fuzzy c-means (FCM) and iterative self-organizing data (ISODATA) clustering algorithms. The proposed method is tested on simulated heart images and on images from nine patients with and without myocardial infarction (MI). The resulting clustered images are compared with MRI delayed-enhancement (DE) viability images for determining MI. Also, Bland-Altman analysis is conducted between the two methods.

RESULTS: Normal myocardium, infarcted myocardium, and blood are correctly identified using the proposed method. The clustered images correctly identified 90 +/- 4% of the pixels defined as infarct in the DE images. In addition, 89 +/- 5% of the pixels defined as infarct in the clustered images were also defined as infarct in DE images. The Bland-Altman results show no bias between the two methods in identifying MI.

CONCLUSION: The proposed technique allows for objectively identifying divergent heart tissues, which would be potentially important for clinical decision-making in patients with MI.

Author List

Ibrahim el-SH, Weiss RG, Stuber M, Spooner AE, Osman NF

MESH terms used to index this publication - Major topics in bold

Computer Simulation
Contrast Media
Fuzzy Logic
Gadolinium DTPA
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Myocardial Infarction