Hierarchical Template Matching for 3D Myocardial Tracking and Cardiac Strain Estimation
Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain...
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| Published in | Scientific reports Vol. 9; no. 1; pp. 12450 - 13 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
28.08.2019
Nature Publishing Group |
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| Online Access | Get full text |
| ISSN | 2045-2322 2045-2322 |
| DOI | 10.1038/s41598-019-48927-2 |
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| Abstract | Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers. |
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| AbstractList | Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers.Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers. Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers. |
| ArticleNumber | 12450 |
| Author | Tiwari, Manoj K. Bhudia, Sunil K. Arvanitis, Theodoros N. Palit, Arnab Ferrante, Enzo Bhalodiya, Jayendra M. Williams, Mark A. |
| Author_xml | – sequence: 1 givenname: Jayendra M. surname: Bhalodiya fullname: Bhalodiya, Jayendra M. email: j.bhalodiya@warwick.ac.uk organization: Warwick Manufacturing Group (WMG), University of Warwick – sequence: 2 givenname: Arnab surname: Palit fullname: Palit, Arnab organization: Warwick Manufacturing Group (WMG), University of Warwick – sequence: 3 givenname: Enzo orcidid: 0000-0002-8500-788X surname: Ferrante fullname: Ferrante, Enzo organization: Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional, sinc(i), FICH-UNL/CONICET – sequence: 4 givenname: Manoj K. surname: Tiwari fullname: Tiwari, Manoj K. organization: Indian Institute of Technology Kharagpur – sequence: 5 givenname: Sunil K. surname: Bhudia fullname: Bhudia, Sunil K. organization: Royal Brompton and Harefield NHS Foundation Trust, SW3 6NP – sequence: 6 givenname: Theodoros N. orcidid: 0000-0001-5473-135X surname: Arvanitis fullname: Arvanitis, Theodoros N. organization: Institute of Digital Healthcare, WMG, University of Warwick – sequence: 7 givenname: Mark A. surname: Williams fullname: Williams, Mark A. organization: Warwick Manufacturing Group (WMG), University of Warwick |
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TaylorCCMeasures of Similarity between Two Images AuthorSpat. Stat. Imaging19912038239110.1214/lnms/1215460513 A. 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| Title | Hierarchical Template Matching for 3D Myocardial Tracking and Cardiac Strain Estimation |
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