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A Feature-Based Morphing Methodology for In-Vivo Strain Assessment in Biological Structures

[+] Author Affiliations
Alessandro Satriano, Elena S. Di Martino

University of Calgary, Calgary, AB, Canada

Simone Rivolo

King’s College London, London, UK

Paper No. SBC2013-14820, pp. V01AT13A028; 2 pages
  • ASME 2013 Summer Bioengineering Conference
  • Volume 1A: Abdominal Aortic Aneurysms; Active and Reactive Soft Matter; Atherosclerosis; BioFluid Mechanics; Education; Biotransport Phenomena; Bone, Joint and Spine Mechanics; Brain Injury; Cardiac Mechanics; Cardiovascular Devices, Fluids and Imaging; Cartilage and Disc Mechanics; Cell and Tissue Engineering; Cerebral Aneurysms; Computational Biofluid Dynamics; Device Design, Human Dynamics, and Rehabilitation; Drug Delivery and Disease Treatment; Engineered Cellular Environments
  • Sunriver, Oregon, USA, June 26–29, 2013
  • Conference Sponsors: Bioengineering Division
  • ISBN: 978-0-7918-5560-7
  • Copyright © 2013 by ASME


It is often important, for diagnostic purposes, to evaluate quantitatively the motion undergone by a biological structure, starting from a viable tomographic imaging technique, such as Computed Tomography (CT) or Magnetic Resonance (MR). This is often associated with the need of the clinical personnel to perform an evaluation of a risk factor associated with pathology, e.g. ventricle performance [1]. As of today, the problem has been approached by using the magnetic resonance (MR) tagging technique [2] or experimentally by determining the location of a series of surgically implanted markers in each temporal phase [3]. The latter procedure is naturally very invasive, while MR tagging requires the use of sophisticated MR sequences that are rarely employed in standard care. Multi-detector row computer tomography (CT) scanners (routinely used in cardiac pathology diagnosis) as well as routine cine-MR sequences, on the other hand, allow dynamic imaging of the heart and large vessels with cardiac gating. In order to exploit these dynamic sequences, we have developed a tag-less method to estimate local strains from dynamic tomography gated images.

Copyright © 2013 by ASME



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