Why the study?
Peak velocity profiles extracted from Doppler echocardiographic images are useful for estimating cardiac time intervals and establishing boundary conditions for computational hemodynamic studies.
A novel digital signal processing algorithm using combined thresholding methods may provide objective estimation of peak velocities and cardiac time intervals from Doppler echocardiography.
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May support objective Doppler analysis in research; leaves open prospective clinical validation.
This study aims at developing a digital signal processing algorithm to extract positive and negative peak velocity profiles from Doppler echocardiographic images. These profiles are useful in estimating cardiac time intervals and establishing realistic boundary conditions for computational hemodynamic studies. The proposed image processing algorithm is based on two different thresholding methods. The histograms of image intensity function were used to help threshold values selection so that the algorithm yields velocity profiles properly represent Doppler shift envelopes. One of the thresholding methods tended to provide the lower-limit (i.e. underestimate) of the velocity profile, while the second tended to provide the upper-limit of the velocity profile (i.e., overestimate). The final peak velocity profiles were estimated from the combination of the estimates from both thresholding methods. The peak velocity profiles were then qualitatively compared with the results of the standard edge detection methods such as Canny and Prewitt approximations. The proposed automated approach might be helpful for objective estimation of peak velocities and cardiac time intervals.
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Taebi et al. (2018) studied this question.
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