Ferraiuoli, P, Fenner, J.W. and Narracott, A.J. (2017) Analysis of Speckle Pattern Quality and Uncertainty for Cardiac Strain Measurements Using 3D Digital Image Correlation. In: Proceedings of the VI ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing. ECCOMAS: European Congress on Computational Methods in Applied Sciences and Engineering, 18-20 Oct 2017, Porto, Portugal. Lecture Notes in Computational Vision and Biomechanics, 27 . Springer , pp. 883-892.
Abstract
Measurement of full-field cardiac strain using optical methods has potential application to validate ultrasound measurements ex vivo, confirming their suitability for accurate in vivo strain imaging. This study describes the use of an effective technique to create a speckle pattern over the surface of a porcine heart for ex vivo experiments with the 3D digital image correlation (DIC) method. We characterised the quality of the speckle pattern applied on the cardiac surface by analysis of speckle size and evaluated the baseline uncertainty of 3D-DIC technique using a zero-strain test, applying rigid-body motion to position the marked sample at four locations. Strain errors were reported at a high spatial resolution (~128 µm) and were evaluated over a range of subset sizes. For subset size greater than 29 pixels the strain error was less than 1% making the baseline uncertainty of the 3D-DIC system acceptable to measure strains on the cardiac surface of the order 10%.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer International Publishing AG 2018. |
Keywords: | digital image correlation; speckle pattern; zero-strain test; cardiac imaging; soft tissues |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Infection, Immunity and Cardiovascular Disease |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 VPH CaSE 642612 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Nov 2017 09:43 |
Last Modified: | 22 Nov 2017 09:43 |
Published Version: | https://doi.org/10.1007/978-3-319-68195-5_96 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computational Vision and Biomechanics |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-68195-5_96 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:123891 |