Medical image segmentation using analysis of isolable-contour maps.

Journal Article (Journal Article)

A common challenge for automated segmentation techniques is differentiation between images of close objects that have similar intensities, whose boundaries are often blurred due to partial-volume effects. We propose a novel approach to segmentation of two-dimensional images, which addresses this challenge. Our method, which we call intrinsic shape for segmentation (ISeg), analyzes isolabel-contour maps to identify coherent regions that correspond to major objects. ISeg generates an isolabel-contour map for an image by multilevel thresholding with a fine partition of the intensity range. ISeg detects object boundaries by comparing the shape of neighboring isolabel contours from the map. ISeg requires only little effort from users; it does not require construction of shape models of target objects. In a formal validation with computed-tomography angiography data, we showed that ISeg was more robust than conventional thresholding, and that ISeg's results were comparable to results of manual tracing.

Full Text

Duke Authors

Cited Authors

  • Shiffman, S; Rubin, GD; Napel, S

Published Date

  • November 2000

Published In

Volume / Issue

  • 19 / 11

Start / End Page

  • 1064 - 1074

PubMed ID

  • 11204844

International Standard Serial Number (ISSN)

  • 0278-0062

Digital Object Identifier (DOI)

  • 10.1109/42.896782

Language

  • eng

Conference Location

  • United States