AbstractID: 7678 Title: Method For Reducing Uncertainty In Selecting Organ Boundary Points for CT
Image-based Organ Registration
Image based organ registration is one of the most important components in the implementation of image feedback adaptive
radiotherapy. Biomechanical model and finite element method (FEM) have been introduced to solve this registration problem by
calculating organ deformation. In the calculation, one of critical issues is the potential uncertainty in selecting organ boundary points
among different 3D image sets. To reduce this uncertainty, an optimization method was developed. In the method, boundary point
locations on deforming organ surfaces are defined as searching variables. A cost function is defined as the total work (energy)
consumed during organ motion/deformation. Constraints of organ surface stress are introduced to ensure that the stress distribution in
calculation is close to the one in human organs with normal physiological status. First, we select initial boundary points such that they
are evenly distributed on the organ surfaces from user defined fiducial points. Then, we use FEM to calculate the stress distribution
over the organ surface. The optimal boundary points are then iteratively searched based on the surface stress distribution calculated
using the FEM. This optimization method was tested with a computer simulation using organs of interest for prostate cancer treatment.
The results demonstrate that boundary selection discrepancy can be reduced significantly after a few iterations.
Support in part by CA71785