Share Email Print
cover

Proceedings Paper

Image segmentation using the student's t-test and the divergence of direction on spherical regions
Author(s): George Stetten; Samantha Horvath; John Galeotti; Gaurav Shukla; Bo Wang; Brian Chapman
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

We have developed a new framework for analyzing images called Shells and Spheres (SaS) based on a set of spheres with adjustable radii, with exactly one sphere centered at each image pixel. This set of spheres is considered optimized when each sphere reaches, but does not cross, the nearest boundary of an image object. Statistical calculations at varying scale are performed on populations of pixels within spheres, as well as populations of adjacent spheres, in order to determine the proper radius of each sphere. In the present work, we explore the use of a classical statistical method, the student's t-test, within the SaS framework, to compare adjacent spherical populations of pixels. We present results from various techniques based on this approach, including a comparison with classical gradient and variance measures at the boundary. A number of optimization strategies are proposed and tested based on pairs of adjacent spheres whose size are controlled in a methodical manner. A properly positioned sphere pair lies on opposite sides of an object boundary, yielding a direction function from the center of each sphere to the boundary point between them. Finally, we develop a method for extracting medial points based on the divergence of that direction function as it changes across medial ridges, reporting not only the presence of a medial point but also the angle between the directions from that medial point to the two respective boundary points that make it medial. Although demonstrated here only in 2D, these methods are all inherently n-dimensional.

Paper Details

Date Published: 13 March 2010
PDF: 9 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76233I (13 March 2010); doi: 10.1117/12.844014
Show Author Affiliations
George Stetten, Univ. of Pittsburgh (United States)
Carnegie Mellon Univ. (United States)
Samantha Horvath, Univ. of Pittsburgh (United States)
John Galeotti, Carnegie Mellon Univ. (United States)
Gaurav Shukla, Univ. of Pittsburgh (United States)
Bo Wang, Univ. of Pittsburgh (United States)
Brian Chapman, Univ. of Pittsburgh (United States)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

© SPIE. Terms of Use
Back to Top