Nerve cell segmentation via multi-scale gradient watershed hierarchies

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Automated segmentation of nerve cell in microscopic image is an important task in neural researches. We proposed a multi-scale watershed-based approach to cope with this microscopic image analysis problem. There are three stages in the proposed segmentation algorithm: (1) a multi-scale watershed scheme is used to estimate an initial location of nerve cell nuclei; (2) we can identity nerve cell nuclei according to properties of nerve cell and watershed results in different scale; (3) Once the possible nerve cell is identified as a true one, a fuzzy rule based Active Contour Model (ACM) is applied to find the optimal outer contour. Our approach can segment nerve cell automatically and accurately. The cell detection rates in the experiments are above 95%. Moreover, the fuzzy rule based ACM provides flexible alternative to handle cell contour detection.

Original languageEnglish
Title of host publication28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Pages4310-4313
Number of pages4
DOIs
Publication statusPublished - 2006 Dec 1
Event28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States
Duration: 2006 Aug 302006 Sep 3

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Other

Other28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
CountryUnited States
CityNew York, NY
Period06-08-3006-09-03

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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