User-Driven 3D Mesh Region Targeting

We present a method for the fast selection of a region on a 3D mesh using geometric information. This is done using a weighted arc length minimization with a conformal factor based on the mean curvature of the 3D surface. A careful analysis of the geometric estimation process enables our geometric curve shortening to use a reliable smooth estimate of curvature and its gradient. The result is a robust way for a user to easily interact with particular regions of a 3D mesh construced from medical imaging. In this study, we focus on building a robust and semi-automatic method for extracting selected folds on the cortical surface, specifically for isolating gyri by drawing a curve along the surrounding sulci. It is desirable to make this process semi-automatic because manually drawing a curve through the complex 3D mesh is extremely tedious, while automatic methods cannot realistically be expected to select the exact closed contour a user desires for a given dataset. In the technique described here, a user places a handful of seed points surrounding the gyri of interest; an initial curve is made from these points which then evolves to capture the region. We refer to this user-driven procedure as targeting or selection interchangeably. To illustrate the applicability of these methods to other medical data, we also give an example of bone fracture CT surface parcellation.