A novel geodesic distance based clustering approach to delineating boundaries of touching cells

Xu Chen, Yanqiao Zhu, Fuhai Li, Zeyi Zheng, Eric Chang, Jinwen Ma, Stephen T.C. Wong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In this paper, we propose a novel geodesic distance based clustering approach for delineating boundaries of touching cells. In specific, the Riemannian metric is firstly adopted to integrate the spatial distance and intensity variation. Then the distance between any two given pixels under this metric is computed as the geodesic distance in a propagational way, and the K-means-like algorithm is deployed in clustering based on the propagational distance. The proposed method was validated to segment the touching Madin-Darby Canine Kidney (MDCK) epithelial cell images for measuring their N-Ras protein expression patterns inside individual cells. The experimental results and comparisons demonstrate the advantages of the proposed method in massive cell segmentation and robustness to the initial seeds selection, varying intensity contrasts and high cell densities in microscopy images.

Original languageEnglish
Title of host publicationAdvances in Neural Networks, ISNN 2013 - 10th International Symposium on Neural Networks, Proceedings
Pages315-322
Number of pages8
EditionPART 2
DOIs
StatePublished - Aug 1 2013
Externally publishedYes
Event10th International Symposium on Neural Networks, ISNN 2013 - Dalian, China
Duration: Jul 4 2013Jul 6 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7952 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Symposium on Neural Networks, ISNN 2013
CountryChina
CityDalian
Period07/4/1307/6/13

Keywords

  • Cell Segmentation
  • Clustering Analysis
  • Distance Propagation
  • Riemannian Metric

Fingerprint Dive into the research topics of 'A novel geodesic distance based clustering approach to delineating boundaries of touching cells'. Together they form a unique fingerprint.

Cite this