Key result
A fully automated watershed segmentation technique for basal left ventricle slices in cine cardiac MRI demonstrated high accuracy compared to manual contours, with a computation time of 0.027s per image and 100% reproducibility.
Why the study?
Does a watershed segmentation technique accurately segment the basal left ventricle in cine cardiac MRI compared to manual expert contours?
Does a watershed segmentation technique accurately segment the basal left ventricle in cine cardiac MRI compared to manual expert contours?
A fully automated watershed segmentation technique for basal slices in cine cardiac MRI is fast, accurate, and reproducible compared to manual expert contours.
May enable rapid automated basal LV analysis; extends segmentation methods but leaves open clinical adoption pending validation.
To quantitatively analyze global and regional cardiac function from MR, clinical parameters such as ejection fraction (EF) and volumes are required. These depend upon accurate delineation of endo- and epicardial contours of the left ventricle (LV). Previous work [ 1 ] has demonstrated the difficulty of accurate LV segmentation, especially in basal slices where the LV outflow tract (LVOT) interrupts continuous myocardial contours. A novel method for the robust, accurate and fully automatic LV segmentation from short axis (SA) cine MR images is presented in this study that applies watershed technique to solve basal slice segmentation.
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Lu et al. (2011) studied Heart failure, left ventricular hypertrophy, and healthy controls (n=146). Watershed segmentation algorithm vs. Manually drawn expert contours was evaluated on Accuracy of automated segmentation compared to manual expert contours (Average perpendicular distance and Dice metric). A fully automated watershed segmentation technique for basal left ventricle slices in cine cardiac MRI demonstrated high accuracy compared to manual contours, with a computation time of 0.027s per image and 100% reproducibility.
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