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An abstract of the article "Automatic myocardium segmentation of LGE MRI by deformable models with prior shape data," by YingLi Lu and colleagues is presented.

An abstract of the conference paper "Semi-automated analysis of infarct heterogeneity on DE-MRI using graph cuts," by YingLi Lu and colleagues is presented.

An abstract of the paper "Watershed Segmentation of Basal Left Ventricle for Quantitation of Cine Cardiac MRI Function," by Yingli Lu and colleagues, from the 2011 SCMR/Euro CMR Joint Scientific Sessions, held in Nice, France, from February 3-6, 2011, is presented.

Rationale and Objectives: A fully automated left ventricle segmentation method for the functional analysis of cine short axis (SAX) magnetic resonance (MR) images was developed, and its performance evaluated with 133 studies of subjects with diverse pathology: ischemic heart failure (n=34), non-ischemic heart failure (n=30), hypertrophy (n=32), and healthy (n=37)., Materials and Methods: The proposed automatic method locates the left ventricle (LV), then for each image detects the contours of the endocardium, epicardium, papillary muscles and trabeculations. Manually and automatically determined contours and functional parameters were compared quantitatively., Results: There was no significant difference between automatically and manually determined end systolic volume (ESV), end diastolic volume (EDV), ejection fraction (EF) and left ventricular mass (LVM) for each of the four groups (paired sample t-test, α=0.05). The automatically determined functional parameters showed high correlations with those derived from manual contours, and the Bland-Altman analysis biases were small (1.51 mL, 1.69 mL, -0.02%, -0.66 g for ESV, EDV, EF and LVM, respectively)., Conclusions: The proposed technique automatically and rapidly detects endocardial, epicardial, papillary muscles' and trabeculations' contours providing accurate and reproducible quantitative MRI parameters, including LV mass and EF.

In this work, we propose a semi-automated myocardial infarction quantification method for cardiac contrast delayed enhancement magnetic resonance images (DE-MRI). Advantages of this method include that it reduces manual contouring of the left ventricle, obviates a remote myocardium region, and automatically distinguishes infarct, healthy and heterogeneous ("gray zone") tissue despite variability in intensity and noise across images. Quantitative evaluation results showed that the automatically determined infarct core and gray zone size have high correlation with that derived from the averaged results of the manual full width at half maximum (FWHM) methods (R(2)=0.99 for infarct core and gray zone size). Compared with the manual method, a much better reproducibility was achieved with the proposed algorithm and it shortens the evaluation time to one second per image, compared with 2-5 min per image for the manual method.