Department of Mathematics
 Search | Help | Login | pdf version | printable version

Math @ Duke



Publications [#264993] of Guillermo Sapiro

Papers Published

  1. Rathi, Y; Olver, P; Sapiro, G; Tannenbaum, A, Affine invariant surface evolutions for 3D image segmentation, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 6064 (April, 2006), SPIE, ISSN 0277-786X [doi]
    (last updated on 2019/06/25)

    In this paper we present an algorithm for 3D medical image segmentation based on an affine invariant flow. The algorithm is simple to implement and semi-automatic. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The surface flow is obtained by minimizing a global energy with respect to an affine invariant metric. Affine invariant edge detectors for 3-dimensional objects are also computed which have the same qualitative behavior as the Euclidean edge detectors. Results on artificial and real MRI images show that the algorithm performs well, both in terms of accuracy and robustness to noise. © 2006 SPIE-IS&T.
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320