ITR/CCR: Geometric Surface Processing Tools for Analysis of Biological Data

University Of Utah, Salt Lake City UT

Investigators

Abstract

EIA-0313268 Ross T. Whitaker University of Utah Project Summary The goal of this project is to develop a new set of computational tools for processing and analyzing surfaces that are extracted from complex biological data sets. The purpose is closing the gap that prevents the widespread use of geometric surface-filtering tools in biological and medical applications. This gap exists for two reasons. The first is that these sophisticated and powerful tools for filtering surfaces rely on numerical algorithms that are computationally demanding. The second reason is that biological applications require not only surface filtering, but a set of complimentary tools for higher-level processing. Thus, the proposed work will address both issues, better filtering algorithms and higher-level processing tools. The broader impact of this work is as follows. Agro wing number of scientific and medical investigations rely on studying populations of subjects through 3D imaging. Such studies produce databases of images and therefore require better tools for extracting meaningful information from the individual images and quantifying geometric properties in order to make scientific conclusions. Previous work focused on extracting the surfaces that are embedded in this 3D data, but many of the relevant biological questions pertain to the geometric properties of those surfaces. The investigators envision a powerful new toolbox that will enable scientists, engineers, and clinicians to process 3D surface data. More specifically, the PI for the proposed work is engaged in several different projects that have such requirements, and thus the proposed work has concrete implications for ongoing research with direct applications. Furthermore, the proposed work has an educational element that includes multidisciplinary educational opportunities for postdoctoral candidates and graduate students and a program by which we will expose undergraduate women to leading-edge research in hardware and software for 3D graphics. The proposed work builds upon previous results that generalize the fundamentals of image processing to surfaces. That work produced technologies for surface reconstruction from tomographic data and geometric versions of variational image filters such as Gaussian smoothing, anisotropic diffusion, and high-boost filtering. These developments have broad implications for a variety of problems that entail extracting, analyzing, and visualizing surfaces. To satisfy the goals of this project, the investigators will pursue two areas of research. The first is the development of better algorithms for variational surface filtering. The focus of this part of the work is on speed and accuracy. The investigators will examine more efficient and accurate numerical techniques and surface representations, as well as implementations on commodity graphics cards. The second area of research is the development of new algorithms for analysis. This work will focus on surface segmentation, feature detection, shape quantification, and surface matching. All of this work will be implemented in conjunction with the Insight Toolkit, an open-source, NIH-sponsored software framework for multidimensional image processing.