Why the study?
Does intensity-based texture analysis improve the segmentation of scarred myocardium in LG enhanced CMR images compared to manual segmentation?
Does intensity-based texture analysis improve the segmentation of scarred myocardium in LG enhanced CMR images compared to manual segmentation?
A new intensity-based texture analysis technique provides high sensitivity and specificity for automatic segmentation of myocardial scar in LG enhanced CMR images compared to manual expert segmentation.
May aid automated scar segmentation in LG-CMR; leaves open prospective validation before clinical adoption.
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.
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Kotu et al. (2011) studied this question.
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