Bhalodiya JM, Palit A, Ferrante E, Tiwari MK, Bhudia SK, Arvanitis TN, Williams MA.
Scientific Reports (2019) 9: 12450
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.
Chair of e-Health Innovation and Head of Research, Institute of Digital Healthcare at The University of Warwick
Professor Theodoros Arvanitis’s HDR UK related research will focus on: Making sense of health and wellbeing data, in order to improve public health and clinical knowledge in the...
Health Data Research UK researchers develop innovative tools and technologies needed to unlock knowledge from complex and diverse health data, to address some of the biggest health challenges that...