Back to Search
Start Over
An optimisation-based iterative approach for speckle tracking echocardiography
- Source :
- Medical & Biological Engineering & Computing
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- Speckle tracking is the most prominent technique used to estimate the regional movement of the heart based on echocardiograms. In this study, we propose an optimised-based block matching algorithm to perform speckle tracking iteratively. The proposed technique was evaluated using a publicly available synthetic echocardiographic dataset with known ground-truth from several major vendors and for healthy/ischaemic cases. The results were compared with the results from the classic (standard) two-dimensional block matching. The proposed method presented an average displacement error of 0.57 pixels, while classic block matching provided an average error of 1.15 pixels. When estimating the segmental/regional longitudinal strain in healthy cases, the proposed method, with an average of 0.32 ± 0.53, outperformed the classic counterpart, with an average of 3.43 ± 2.84. A similar superior performance was observed in ischaemic cases. This method does not require any additional ad hoc filtering process. Therefore, it can potentially help to reduce the variability in the strain measurements caused by various post-processing techniques applied by different implementations of the speckle tracking. Graphical Abstract Standard block matching versus proposed iterative block matching approach.
- Subjects :
- Matching (statistics)
Databases, Factual
Computer science
Myocardial Ischemia
Biomedical Engineering
Speckle tracking echocardiography
030204 cardiovascular system & hematology
Tracking (particle physics)
030218 nuclear medicine & medical imaging
Intelligent-systems
03 medical and health sciences
Speckle pattern
0302 clinical medicine
Image Processing, Computer-Assisted
Humans
Diagnosis, Computer-Assisted
Block (data storage)
Block-matching algorithm
Pixel
Myocardial deformation
business.industry
Process (computing)
Strain imaging
Pattern recognition
G400 Computer Science
clinical-care
Computer Science Applications
Echocardiography
Original Article
Artificial intelligence
business
Algorithms
Subjects
Details
- ISSN :
- 17410444 and 01400118
- Volume :
- 58
- Database :
- OpenAIRE
- Journal :
- Medical & Biological Engineering & Computing
- Accession number :
- edsair.doi.dedup.....fd7dc88378a4416d54cd1d281ac4eb76
- Full Text :
- https://doi.org/10.1007/s11517-020-02142-8