Several speckle tracking methods have been proposed for noninvasive and quantitative evaluation of tissue motion. Since the low temporal resolution causes a large myocardial motion in the elevational direction and a large deformation, two-dimensional (2D) speckle tracking at a high frame rate is desirable for accurate estimation of myocardial contraction and relaxation. 2D speckle tracking at a high frame rate requires a high computational load, and the large suppression of calculation time is, therefore, essential for clinical use. In the present study, we investigate the minimum frame rate required for the estimation of myocardial contraction and relaxation. Furthermore, we employ a parallel computing principle using a graphical processing unit (GPU) system with 2,496 streaming processors to decrease the calculation time effectively. The employment of a parallel computing principle with a GPU system successfully decreased the calculation time to 1/50 of that using a desktop PC with a CPU. When the number of tracking points is 64, the calculation time was decreased to 28.7 s for the estimation during 1 s at a frame rate of 287 Hz, indicating that the proposed method with a GPU system has a potential to realize a near real-time estimation of myocardial contraction and relaxation.
|Number of pages
|IEEJ Transactions on Electronics, Information and Systems
|Published - 2017
- Graphical processing unit (GPU)
- Myocardial contraction/relaxation property
- Speckle tracking
- Two-dimensional (2D) displacement estimation