User intervention based segmentation of Myocardium In cardiac cine MRI images

For the past one and a half decade, Magnetic Resonance Imaging (MRI) has become a preferred imaging technique for examination of cardiac morphology and its functions in humans. The heart cavities segmentation in MRI is still a challenge to be resolved due to the greater unpredictability of the images among patients and the characteristics of cardiac MR images. We present user intervention based semi-automatic method for segmentation in short axis images. The method includes various segmentation methods like graph-cut, watershed and the threshold based segmentation to calculate wall thickness and ejection factor which are of clinical importance. Challenge is to effectively segment epicardium and endocardium boundaries, for effective assessment. We have collected dataset from Sunnybrook Cardiac Data (SCD). The performance of each of the segmentation method is assessed by recording confusion matrix, and calculating sensitivity, specificity and accuracy. We conclude with a discussion of the results obtained which are in favour of graph-cut segmentation and future intended course of action in this field regarding methodological and medical issues.