IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic segmentation of pathological tissues in cardiac MRI
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
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We propose an automatic technique to segment scar and classify the myocardial tissue of the left ventricle from Delay Enhancement (DE) MRI. The method uses multiple region growing with two types of regions and automatic seed initialization. The region growing criteria is based on intensity distance and the seed initialization is based on a thresholding technique. We refine the obtained segmentation with some morphological operators and geometrical constraints to further define the infarcted area. Thanks to the use of two types of regions when performing the region growing, we are able to segment and classify the healthy and pathological tissues. We have also a third type of tissue in our classification, which includes tissue areas that deserve special attention from medical experts: border-zone tissue or myocardial segmentation errors.