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Hierarchical template matching for 3D myocardial tracking and cardiac strain estimation

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Bhalodiya, Jayendra Maganbhai, Palit, Arnab, Ferrante, Enzo, Tiwari, Manoj K., Bhudia, Sunil K., Arvanitis, Theodoros N. and Williams, Mark A. (2019) Hierarchical template matching for 3D myocardial tracking and cardiac strain estimation. Scientific Reports, 9 . 12450. doi:10.1038/s41598-019-48927-2

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Official URL: https://doi.org/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.

Item Type: Journal Article
Subjects: Q Science > QM Human anatomy
R Medicine > R Medicine (General)
R Medicine > RC Internal medicine
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Myocardium -- Ultrasonic imaging, Cardiovascular system -- Diseases -- Diagnosis, Three-dimensional imaging in medicine , Three-dimensional imaging
Journal or Publication Title: Scientific Reports
Publisher: Nature Publishing Group
ISSN: 2045-2322
Official Date: 28 August 2019
Dates:
DateEvent
28 August 2019Published
14 August 2019Accepted
4 March 2019Submitted
Volume: 9
Article Number: 12450
DOI: 10.1038/s41598-019-48927-2
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
Health Data Research (HDR) grant [MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
Health Data Research (HDR) grant [EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
Health Data Research (HDR) grant [ESRC] Economic and Social Research Councilhttp://dx.doi.org/10.13039/501100000269
Health Data Research (HDR) grant Department of Health and Social CareUNSPECIFIED
Health Data Research (HDR) grant Chief Scientist Office, Scottish Government Health and Social Care Directoratehttp://dx.doi.org/10.13039/100014589
Health Data Research (HDR) grant Health and Social Care Research and Development Divisionhttp://dx.doi.org/10.13039/501100010756
Health Data Research (HDR) grant Public Health Agencyhttp://dx.doi.org/10.13039/501100001626
Health Data Research (HDR) grant British Heart Foundationhttp://dx.doi.org/10.13039/501100000274
Health Data Research (HDR) grant Wellcome Trusthttp://dx.doi.org/10.13039/100010269
UNSPECIFIEDAXA Research Fundhttp://dx.doi.org/10.13039/501100001961
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