User-driven 3D mesh region targeting

Abstract

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. We describe the applicability of the method for real-time clinician use. 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.

Publication
Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, San Diego, California, United States, 13-18 February 2010
Marc Niethammer
Marc Niethammer
Professor of Computer Science

My research interests include image registration, image segmentation, shape analysis, machine learning, and biomedical applications.

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