Image-Based Motion Correction for Optical Mapping of Cardiac Electrical Activity
Annals of Biomedical Engineering, ISSN: 1573-9686, Vol: 43, Issue: 5, Page: 1235-1246
2015
- 13Citations
- 30Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations13
- Citation Indexes13
- 13
- CrossRef7
- Captures30
- Readers30
- 30
Article Description
Optical mapping, with membrane-bound, voltage-sensitive dyes, is widely used for in vitro recording of cardiac electrical activity. The spatial registration of such maps is lost when the heart moves with respect to a fixed photodetector array and contraction can generate substantial artifact if background fluorescence is not uniformly distributed. While motion artifact is commonly suppressed with electromechanical uncoupling agents, there are circumstances where these are undesirable. This study outlines a novel image-based approach for retrospective motion artifact correction. Isolated Langendorff-supported rat hearts (n = 8), stained with di-4-ANEPPS, were illuminated at 516 ± 14 nm and fluorescent emission (>565 ± 10 nm) was acquired with a charge multiplying CCD camera. Background fluorescence was segmented in successive frames and stabilized using a non-rigid image registration algorithm. The resultant image deformation was used to estimate material point movement on the heart surface, so that total fluorescence could be mapped frame-by-frame to appropriate reference pixels. Finally, residual motion artifact was identified and removed. The effectiveness of this correction method was evaluated over 18 experimental datasets. Signal-to-noise ratio was increased more than fourfold, and activation time and action potential duration (APD) could be estimated at 24% more pixels than in the raw data. The variability of all APD measures was substantially reduced (i.e. APD50 estimated as 83.8 ± 45.8 ms before correction was 52.1 ± 4.7 ms afterward). This approach provides a robust means of recovering optical action potentials in the presence of substantial motion artifact.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84938563454&origin=inward; http://dx.doi.org/10.1007/s10439-014-1172-8; http://www.ncbi.nlm.nih.gov/pubmed/25384833; http://link.springer.com/10.1007/s10439-014-1172-8; https://dx.doi.org/10.1007/s10439-014-1172-8; https://link.springer.com/article/10.1007/s10439-014-1172-8
Springer Science and Business Media LLC
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