DocumentCode
2493949
Title
Segmentation of scarred and non-scarred myocardium in LG enhanced CMR images using intensity-based textural analysis
Author
Kotu, Lasya Priya ; Engan, Kjersti ; Eftestøl, Trygve ; Ørn, Stein ; Woie, Leik
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Univ. of Stavanger, Stavanger, Norway
fYear
2011
fDate
Aug. 30 2011-Sept. 3 2011
Firstpage
5698
Lastpage
5701
Abstract
The Late Gadolinium (LG) enhancement in Cardiac Magnetic Resonance (CMR) imaging is used to increase the intensity of scarred area in myocardium for thorough examination. Automatic segmentation of scar is important because scar size is largely responsible in changing the size, shape and functioning of left ventricle and it is a preliminary step required in exploring the information present in scar. We have proposed a new technique to segment scar (infarct region) from non-scarred myocardium using intensity-based texture analysis. Our new technique uses dictionary-based texture features and dc-values to segment scarred and non-scarred myocardium using Maximum Likelihood Estimator (MLE) based Bayes classification. Texture analysis aided with intensity values gives better segmentation of scar from myocardium with high sensitivity and specificity values in comparison to manual segmentation by expert cardiologists.
Keywords
biomedical MRI; cardiology; image segmentation; image texture; maximum likelihood estimation; medical image processing; muscle; Bayes classification; LG enhanced CMR images; cardiac magnetic resonance; dictionary-based texture features; image segmentation; infarct region; intensity-based textural analysis; intensity-based texture analysis; late gadolinium; maximum likelihood estimator; nonscarred myocardium; scarred myocardium; Dictionaries; Image segmentation; Maximum likelihood estimation; Myocardium; Sensitivity; Training; Vectors; Algorithms; Contrast Media; Gadolinium; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging, Cine; Myocardial Stunning; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location
Boston, MA
ISSN
1557-170X
Print_ISBN
978-1-4244-4121-1
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2011.6091379
Filename
6091379
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