Multiscale detection of curvilinear structures in 2-D and 3-D image data

Th M. Koller, G. Gerig, G. Szekely, D. Dettwiler

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper presents a novel, parameter-free technique for the segmentation and local description of line structures on multiple scales, both in 2-D and 3-D. The algorithm is based on a nonlinear combination of linear filters and searches for elongated, symmetric line structures, while suppressing the response to edges. The filtering process creates one sharp maximum across the line-feature profile and across scale-space. The multiscale response reflects local contrast and is independent of the local width. The filter is steerable in orientation and scale domain, leading to an efficient, parameter-free implementation. A local description is obtained that describes the contrast, the position of the center-line, the width, the polarity, and the orientation of the line. Examples of images from different application domains demonstrate the generic nature of the line segmentation scheme. The 3-D filtering is applied to magnetic resonance volume data in order to segment cerebral blood vessels.

Original languageEnglish (US)
Pages864-869
Number of pages6
StatePublished - 1995
EventProceedings of the 5th International Conference on Computer Vision - Cambridge, MA, USA
Duration: Jun 20 1995Jun 23 1995

Other

OtherProceedings of the 5th International Conference on Computer Vision
CityCambridge, MA, USA
Period6/20/956/23/95

ASJC Scopus subject areas

  • Engineering(all)

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