Share Email Print

Proceedings Paper

Knowledge-based direct 3-D texture segmentation system for confocal microscopic images
Author(s): Zhengping Lang; Zhen Zhang; Randell E. Scarberry; Weimin Shao; Xu-Mei Sun
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In this paper, we present a knowledge-based texture segmentation system for the identification of 3D structures in biomedical images. The segmentation is guided by in Iterative Octree Expansion and (leaf node) Linking control algorithm. The segmentation is performed directly in 3D space which is contrary to that done in common approaches where 3D structures are reconstructed from results of 2D segmentation of a sequence of consecutive, cross-sectional images. Test result of a prototype of this system on real data confocal scanning fluorescence microscopic images of a developing chick embryo heart is reported.

Paper Details

Date Published: 1 March 1991
PDF: 8 pages
Proc. SPIE 1468, Applications of Artificial Intelligence IX, (1 March 1991); doi: 10.1117/12.45521
Show Author Affiliations
Zhengping Lang, Medical Univ. of South Carolina (United States)
Zhen Zhang, Medical Univ. of South Carolina (United States)
Randell E. Scarberry, Medical Univ. of South Carolina (United States)
Weimin Shao, Medical Univ. of South Carolina (United States)
Xu-Mei Sun, Medical Univ. of South Carolina (United States)

Published in SPIE Proceedings Vol. 1468:
Applications of Artificial Intelligence IX
Mohan M. Trivedi, Editor(s)

© SPIE. Terms of Use
Back to Top