A Modified Fuzzy Inference Rule-Based Model for 3D Speckle Tracking
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s40815-022-01428-3.pdf
Reference26 articles.
1. Crosby, J., Amundsen, B.H., Hergum, T., Remme, E.W., Langeland, S., Torp, H.: 3-D speckle tracking for assessment of regional left ventricular function. Ultrasound Med. Biol. 35(3), 458–471 (2009). https://doi.org/10.1016/j.ultrasmedbio.2008.09.011
2. Alessandrini, M., et al.: Detailed evaluation of five 3D speckle tracking algorithms using synthetic echocardiographic recordings. IEEE Trans. Med. Imaging 35(8), 1915–1926 (2016). https://doi.org/10.1109/TMI.2016.2537848
3. Chen, X., et al.: 3-D correlation-based speckle tracking. Ultrason. Imaging 27(1), 21–36 (2005). https://doi.org/10.1177/016173460502700102
4. Somphone, O., et al.: Fast myocardial motion and strain estimation in 3D cardiac ultrasound with Sparse Demons. Proc. Intl. Symp. Biomed. Imaging 1, 1182–1185 (2013). https://doi.org/10.1109/ISBI.2013.6556691
5. Heyde, B., Alessandrini, M., Hermans, J., Barbosa, D., Claus, P., Dhooge, J.: Anatomical image registration using volume conservation to assess cardiac deformation from 3D ultrasound recordings. IEEE Trans. Med. Imaging 35(2), 501–511 (2016). https://doi.org/10.1109/TMI.2015.2479556
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