Share Email Print

Proceedings Paper

Inverse methods for 3D quantitative optical coherence elasticity imaging (Conference Presentation)
Author(s): Li Dong; Philip Wijesinghe; Nicholas Hugenberg; David D. Sampson; Peter R. T. Munro; Brendan F. Kennedy; Assad A. Oberai

Paper Abstract

In elastography, quantitative elastograms are desirable as they are system and operator independent. Such quantification also facilitates more accurate diagnosis, longitudinal studies and studies performed across multiple sites. In optical elastography (compression, surface-wave or shear-wave), quantitative elastograms are typically obtained by assuming some form of homogeneity. This simplifies data processing at the expense of smearing sharp transitions in elastic properties, and/or introducing artifacts in these regions. Recently, we proposed an inverse problem-based approach to compression OCE that does not assume homogeneity, and overcomes the drawbacks described above. In this approach, the difference between the measured and predicted displacement field is minimized by seeking the optimal distribution of elastic parameters. The predicted displacements and recovered elastic parameters together satisfy the constraint of the equations of equilibrium. This approach, which has been applied in two spatial dimensions assuming plane strain, has yielded accurate material property distributions. Here, we describe the extension of the inverse problem approach to three dimensions. In addition to the advantage of visualizing elastic properties in three dimensions, this extension eliminates the plane strain assumption and is therefore closer to the true physical state. It does, however, incur greater computational costs. We address this challenge through a modified adjoint problem, spatially adaptive grid resolution, and three-dimensional decomposition techniques. Through these techniques the inverse problem is solved on a typical desktop machine within a wall clock time of ~ 20 hours. We present the details of the method and quantitative elasticity images of phantoms and tissue samples.

Paper Details

Date Published: 24 April 2017
PDF: 1 pages
Proc. SPIE 10067, Optical Elastography and Tissue Biomechanics IV, 100670S (24 April 2017); doi: 10.1117/12.2252600
Show Author Affiliations
Li Dong, Rensselaer Polytechnic Institute (United States)
Philip Wijesinghe, The Univ. of Western Australia (Australia)
Nicholas Hugenberg, Rensselaer Polytechnic Institute (United States)
David D. Sampson, The Univ. of Western Australia (Australia)
Peter R. T. Munro, Univ. College London (United Kingdom)
The Univ. of Western Australia (Australia)
Brendan F. Kennedy, Harry Perkins Institute of Medical Research (Australia)
The Univ. of Western Australia (Australia)
Assad A. Oberai, Rensselaer Polytechnic Institute (United States)

Published in SPIE Proceedings Vol. 10067:
Optical Elastography and Tissue Biomechanics IV
Kirill V. Larin; David D. Sampson, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?