Automatic generation of boundary conditions using demons non-rigid image registration for use in 3D modality-independent elastography.

Abstract

Modality-independent elastography (MIE) is a method of elastography that reconstructs the elastic properties of tissue using images acquired under different loading conditions and a biomechanical model. Boundary conditions are a critical input to the algorithm, and are often determined by time-consuming point correspondence methods requiring manual user input. Unfortunately, generation of accurate boundary conditions for the biomechanical model is often difficult due to the challenge of accurately matching points between the source and target surfaces and consequently necessitates the use of large numbers of fiducial markers. This study presents a novel method of automatically generating boundary conditions by non-rigidly registering two image sets with a Demons diffusion-based registration algorithm. The use of this method was successfully performed in silico using magnetic resonance and X-ray computed tomography image data with known boundary conditions. These preliminary results produced boundary conditions with accuracy of up to 80% compared to the known conditions. These boundary conditions were utilized within a 3D MIE reconstruction to determine an elasticity contrast ratio between tumor and normal tissue. Two phantom experiments were conducted to further test the accuracy of the demons boundary conditions and the MIE reconstruction arising from the use of these conditions. Preliminary results show a reasonable characterization of the material properties on this first attempt and a significant improvement in the automation level and viability of the method.