Speed-invariant region growing: Its properties and applications to 3-D medical CT images

S. Y. Wan*, E. Nung

*Corresponding author for this work

Research output: Contribution to conferenceConference Paperpeer-review

2 Scopus citations


The objective of image segmentation is to define disjoint regions of interest from a digital image. Region-growing approach among many segmentation methods employs connectivity, local homogeneity, and the other image-dependent characteristics as features for segmentation. A three-dimensional CT (computed tomography) image can be formed by imaging a contrast-injected subject. The spreading scenario is similar to region growing. The intensity degradation along the contrast-spreading paths requires local-homogeneity information for better segmentation. In this paper, we present the properties of a symmetric region-growing (SymRG) approach that is suitable for processing medical CT images. We briefly review the concept and definitions of SymRG, describe its seed-invariant property and computational separability. These significant factors govern the region-growing behavior (unidirectional region growing and inter-slice merging) and computational and memory-usage efficiency. We also propose a general SymRG algorithm for any dimensional images and demonstrate experimental results.

Original languageEnglish
Number of pages4
StatePublished - 2001
EventIEEE International Conference on Image Processing (ICIP) 2001 - Thessaloniki, Greece
Duration: 07 10 200110 10 2001


ConferenceIEEE International Conference on Image Processing (ICIP) 2001


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