TEMPORAL INCOHERENCE ELIMINATION FOR 2D COLOR DOPPLER ECHOCARDIOGRAPHY VIA MASKING ALGORITHM.

Terentjev A.B., Vasilyev N.V. Temporal incoherence elimination for 2D color Doppler echocardiography via masking algorithm. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2019, vol. 19, no. 5, pp. 875–882 (in Russian). doi: 10.17586/2226-1494-2019-19-5-875-882

Subject of Research. We introduce a novel method for resolving temporal incoherence in two-dimensional color Doppler echocardiography (2D CDE). Incoherence occurs when the temporal distance between frames is less than frame duration. This happens for frame reordering algorithms, which is a widespread processing method. Existing solution — temporal weighting — requires a lot of time for processing (more than 2 seconds per frame) and is not designed for blood flow data. Method. In the proposed method, the weights are calculated not per pixel, but per image subsector obtained by a specific precomputed mask,utilizing the mechanics of the acquisition process. Pixels with opposite blood flow directions are weighted separately with the further weights comparison. We evaluated the algorithm with 10 animal epicardial 2D CDE datasets of the right ventricle. Main Results. Measurements of differences in execution time and results (pixel intensities) with temporal weighting have shown the order of magnitude increase of processing speed from 0.40 frame/s to 4.63 frame/s. Pixel intensity changes inconsiderably: the average difference value is , maximum with intensity values lying within integer range of. Practical Relevance. The proposed algorithm can be embedded into reordering-based 2D CDE processing pipelines in order to obtain temporally correct results. In addition, the processing speed is close to real-time.

1. Bercoff J., Montaldo G., Loupas T., Savery D., Mézière F., Fink M., Tanter M. Ultrafast compound doppler imaging: providing full blood flow characterization. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2011, vol. 58, no. 1, pp. 134–147. doi: 10.1109/TUFFC.2011.1780
2. Osmanski B.-F., Pernot M., Fink M., Tanter M. In vivo trans- thoracic ultrafast Doppler imaging of left intraventricular blood flow pattern. IEEE International Ultrasonics Symposium (IUS 2013), 2013, pp. 1741–1744. doi: 10.1109/ULTSYM.2013.0444

3. Tong L., Ramalli A., Jasaityte R., Tortoli P., D’Hooge J. Multi- Transmit Beam Forming for Fast Cardiac Imaging–Experimental Validation and In Vivo Application. IEEE Transactions on Medical Imaging, 2014, vol. 33, no. 6, pp. 1205–1219. doi: 10.1109/TMI.2014.2302312
4. Cikes M., Tong L., Sutherland G.R., D’Hooge J. Ultrafast Cardiac Ultrasound Imaging Technical Principles, Applications, and Clinical Benefits. JACC: Cardiovascular Imaging, 2014, vol. 7, no. 8, pp. 812–823. doi: 10.1016/j.jcmg.2014.06.004

5. Chang L.-W., Hsu K.-H., Li P.-C. Graphics processing unit- based high-frame-rate color doppler ultrasound process- ing.  IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2009, vol. 56, no. 9, pp. 1856–1860. doi: 10.1109/TUFFC.2009.1261
6. Perrin D.P., Vasilyev N.V., Marx G.R., Del Nido P.J. Temporal Enhancement of 3D Echocardiography by Frame Reordering. JACC: Cardiovascular Imaging, 2012, vol. 5, no. 3 , pp. 300– 304. doi: 10.1016/j.jcmg.2011.10.006
7. Terentjev A.B., Settlemier S.H., Perrin D.P., Del Nido P.J., Shturts I.V., Vasilyev N.V. Temporal enhancement of two-dimensional color doppler echocardiography. Proceedings of SPIE, 2016, vol. 9784, pp. 97843T. doi: 10.1117/12.2209113

8. Danudibroto A., Bersvendsen J., Mirea O., Gerard O., D’Hooge J., Samset E. Image-based temporal alignment of echocar- diographic sequences. Proceedings of SPIE, 2016, vol. 9790, pp. 97901G. doi: 10.1117/12.2216192
9. Terentjev A.B., Perrin D.P., Settlemier S.H., Zurakowski D., Smirnov P.O., del Nido P.J., Shturts I.V., Vasilyev N.V. Temporal enhancement of 2D color Doppler echocardiography sequences by fragment-based frame reordering and refinement. International  Journal of Computer Assisted Radiology and Surgery, 2019, vol. 14, no. 4, pp. 577–586. doi: 10.1007/s11548-019-01926-0
10. Schneider R.J. Semi-Automatic Delineation of the Mitral Valve from Clinical Four-Dimensional Ultrasound Imaging. Cambridge, Massachusetts: Harvard University, 2011, 166 p.
11. Guide for the Care and Use of Laboratory Animals. Washington, DC: The National Academies Press, 1996.
12. Hill C.R., Bamber J.C., Ter Haar G.R. Physical Principles of Medical Ultrasonics. 2nd ed. John Wiley & Sons, 2002, 511 p. doi: 10.1002/0470093978
13. Zwiebel W.J., Pellerito J.S. Introduction to vascular ultrasonog- raphy. 5th ed. Elsevier, 2005, 674 p.
14. Muth S., Dort S., Sebag I.A., Blais M.-J., Garcia D. Unsupervised dealiasing and denoising of color-Doppler data.  Medical Image Analysis, 2011, vol. 15, no. 4, pp. 577–588.

doi: 10.1016/j.media.2011.03.003
15. Saini K., Dewal M.L, Rohit M. Ultrasound Imaging and Image Segmentation in the area of Ultrasound: A Review. International Journal of Advanced Science and Technology, 2010, vol. 24, pp. 41–60.
 

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