TY - JOUR
T1 - Correlation-based discrimination between cardiac tissue and blood for segmentation of the left ventricle in 3D echocardiographic images
AU - Saris, A.E.
AU - Nillesen, W.W.
AU - Lopata, Richard
AU - de Korte, Chris L.
PY - 2014
Y1 - 2014
N2 - For automated segmentation of 3-D echocardiographic images, incorporation of temporal information may be helpful. In this study, optimal settings for calculation of temporal cross-correlations between subsequent time frames were determined, to obtain the maximum cross-correlation (MCC) values that provided the best contrast between blood and cardiac tissue over the entire cardiac cycle. Both contrast and boundary gradient quality measures were assessed to optimize MCC values with respect to signal choice (radiofrequency or envelope data) and axial window size. Optimal MCC values were incorporated into a deformable model to automatically segment the left ventricular cavity. MCC values were tested against, and combined with, filtered, demodulated radiofrequency data. Results reveal that using envelope data in combination with a relatively small axial window (0.7-1.25?mm) at fine scale results in optimal contrast and boundary gradient between the two tissues over the entire cardiac cycle. Preliminary segmentation results indicate that incorporation of MCC values has additional value for automated segmentation of the left ventricle. World Federation for Ultrasound in Medicine & Biology.
AB - For automated segmentation of 3-D echocardiographic images, incorporation of temporal information may be helpful. In this study, optimal settings for calculation of temporal cross-correlations between subsequent time frames were determined, to obtain the maximum cross-correlation (MCC) values that provided the best contrast between blood and cardiac tissue over the entire cardiac cycle. Both contrast and boundary gradient quality measures were assessed to optimize MCC values with respect to signal choice (radiofrequency or envelope data) and axial window size. Optimal MCC values were incorporated into a deformable model to automatically segment the left ventricular cavity. MCC values were tested against, and combined with, filtered, demodulated radiofrequency data. Results reveal that using envelope data in combination with a relatively small axial window (0.7-1.25?mm) at fine scale results in optimal contrast and boundary gradient between the two tissues over the entire cardiac cycle. Preliminary segmentation results indicate that incorporation of MCC values has additional value for automated segmentation of the left ventricle. World Federation for Ultrasound in Medicine & Biology.
U2 - 10.1016/j.ultrasmedbio.2013.09.025
DO - 10.1016/j.ultrasmedbio.2013.09.025
M3 - Article
C2 - 24412178
SN - 0301-5629
VL - 40
JO - Ultrasound in Medicine and Biology
JF - Ultrasound in Medicine and Biology
IS - 3
ER -