Identification of cell-cycle phases using neural network and steerable filter features

Xiaodong Yang, Houqiang Li, Xiaobo Zhou, Stephen T C Wong

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

Abstract

In this paper, we aim to address the cell phase identification problem, and two important aspects, the feature extraction methods and the classifier design, are discussed. In our study, we first propose extracting high frequency information of different orientations using Steerable filters. Next, we employ a multi-layer neural network using the back-propagation algorithm to replace K-Nearest Neighbor (KNN) classifier which has been implemented in the Cellular Image Quantitator (CELLIQ) system [3]. Experimental results provide a comparison between the proposed steerable filter features and existing regular features which have been used in published papers [3, 5]. From the comparison, it can be concluded that Steerable filter features can effectively represent the cells in different phases and improve the classification accuracy. Neural network also has a better performance than KNN currently deployed in CELLIQ system [3].

Original languageEnglish (US)
Title of host publicationAdvances in Neural Networks - ISNN 2006
Subtitle of host publicationThird International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III
PublisherSpringer-Verlag
Pages702-709
Number of pages8
ISBN (Print)3540344829, 9783540344827
DOIs
StatePublished - Jan 1 2006
Event3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks - Chengdu, China
Duration: May 28 2006Jun 1 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3973 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks
CountryChina
CityChengdu
Period5/28/066/1/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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