Automatic segmentation of cardiac MRI cines validated for long axis views

Segmentation of cardiac magnetic resonance imaging is considered an important application in clinical practice. An automatic algorithm is proposed for segmentation of both endocardial and epicardial boundaries, in long-axis views. The data consisted of 126 patients, yielding 1008 traces. Estimated clinical parameters were highly correlated to gold standard measurements. The error between the automatic tracing and the gold standard was not significantly different than the error between two manual observers. In conclusion, a tool for segmenting the myocardial boundaries in the long-axis views is proposed, which works well, as demonstrated by the validation performed using a clinical dataset.