Medical Image Analysis
Volume 14, Issue 2 , Pages 126-137, April 2010

Estimating zero-strain states of very soft tissue under gravity loading using digital image correlation☆☆☆☆☆☆

Robotics, Automation, Manipulation, and Sensing (RAMS) Laboratory, University of Maryland, College Park, MD 20742, USA

Received 15 April 2009; received in revised form 2 November 2009; accepted 9 November 2009. published online 16 November 2009.

Abstract 

This paper presents several experimental techniques and concepts in the process of measuring mechanical properties of very soft tissue in an ex vivo tensile test. Gravitational body force on very soft tissue causes pre-compression and results in a non-uniform initial deformation. The global digital image correlation technique is used to measure the full-field deformation behavior of liver tissue in uniaxial tension testing. A maximum stretching band is observed in the incremental strain field when a region of tissue passes from compression and enters a state of tension. A new method for estimating the zero-strain state is proposed: the zero strain position is close to, but ahead of the position of the maximum stretching band, or in other words, the tangent of a nominal stress–stretch curve reaches minimum at . The approach, to identify zero strain by using maximum incremental strain, can be implemented in other types of image-based soft tissue analysis. The experimental results of 10 samples from seven porcine livers are presented and material parameters for the Ogden model fit are obtained. The finite element simulation based on the fitted model confirms the effect of gravity on the deformation of very soft tissue and validates our approach.

Keywords: Soft tissue modeling, Digital image correlation (DIC), Liver tissue, Strain measurement, Mechanical properties, Tension experiment, Zero strain or zero stress reference

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☆ Portions reprinted, with permission, from: “Zhan Gao, Kevin Lister, and Jaydev P. Desai, 2008. Constitutive modeling of liver tissue: Experiment and theory. In: 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2008, pp. 477–482. October 19–22, 2008, Scottsdale, AZ” ©2008 IEEE.

☆☆ Portions reprinted, with permission, from: “Zhan Gao, Theodore Kim, Doug L. James, Jaydev P. Desai, 2009. Semi-Automated Soft-Tissue Acquisition and Modeling for Surgical Simulation. In: 5th Annual IEEE Conference on Automation Science and Engineering, CASE 2009, pp. 268–273. August 22–25, 2009, Bangalore, India.” ©2009 IEEE.

☆☆☆ With kind permission from Springer Science+Business Media: Annals of Biomedical Engineering, Constitutive modeling of liver tissue: experiment and theory, 2009, DOI: 10.1007/s10439-009-9812-0, Zhan Gao, Kevin Lister, Jaydev P. Desai, Figs. 3 and 4, which are Figs. 1 and 2 in this paper.

PII: S1361-8415(09)00139-X

doi:10.1016/j.media.2009.11.002

Medical Image Analysis
Volume 14, Issue 2 , Pages 126-137, April 2010

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