Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges

Volume 7746 of the series Lecture Notes in Computer Science pp 87-96

Mixture-Model-Based Segmentation of Myocardial Delayed Enhancement MRI

  • Anja HennemuthAffiliated withCarnegie Mellon UniversityFraunhofer MEVIS
  • , Ola FrimanAffiliated withCarnegie Mellon UniversityFraunhofer MEVIS
  • , Markus HuellebrandAffiliated withCarnegie Mellon UniversityFraunhofer MEVIS
  • , Heinz-Otto PeitgenAffiliated withCarnegie Mellon UniversityFraunhofer MEVIS

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Myocardial viability assessment is an important task in the diagnosis of coronary heart disease. The measurement of the delayed enhancement effect, the accumulation of contrast agent in defective tissue, has become the gold standard for detecting necrotic tissue with MRI. The purpose of the presented work was to provide a segmentation and quantification method for delayed enhancement MRI. To this end, a suitable mixture model for the myocardial intensity distribution is determined based on expectation maximization and the comparison of the fit accuracy. The subsequent watershed-based segmentation uses the intensity threshold information derived from this model. Preliminary results are derived from an analysis of datasets provided by the STACOM challenge organizers. The segmentation provided reasonable results in all datasets, but the method strongly depends on the underlying myocardium segmentation.