Towards automated cellular image segmentation for RNAi genome-wide screening

Xiaobo Zhou, K. Y. Liu, P. Bradley, N. Perrimon, Stephen T. Wong

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

41 Scopus citations

Abstract

The Rho family of small GTPases is essential for morphological changes during normal cell development and migration, as well as during disease states such as cancer. Our goal is to identify novel effectors of Rho proteins using a cell-based assay for Rho activity to perform genome-wide functional screens using double stranded RNA (dsRNAs) interference. We aim to discover genes could cause the cell phenotype changed dramatically. Biologists currently attempt to perform the genome-wide RNAi screening to identify various image phenotypes. RNAi genome-wide screening, however, could easily generate more than a million of images per study, manual analysis is thus prohibitive. Image analysis becomes a bottleneck in realizing high content imaging screens. We propose a two-step segmentation approach to solve this problem. First, we determine the center of a cell using the information in the DNA-channel by segmenting the DNA nuclei and the dissimilarity function is employed to attenuate the over-segmentation problem, then we estimate a rough boundary for each cell using a polygon. Second, we apply fuzzy c-means based multi-threshold segmentation and sharpening technology; for isolation of touching spots, marker-controlled watershed is employed to remove touching cells. Furthermore, Voronoi diagrams are employed to correct the segmentation errors caused by overlapping cells. Image features arc extracted for each cell. K-nearest neighbor classifier (KNN) is employed to perform cell phenotype classification. Experimental results indicate that the proposed approach can be used to identify cell phenotypes of RNAi genome-wide screens.

Original languageEnglish
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
PublisherSpringer-Verlag
Pages885-892
Number of pages8
Volume3749 LNCS
ISBN (Print)3540293272, 9783540293279
DOIs
StatePublished - Dec 1 2005
Externally publishedYes
Event8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - Palm Springs, CA, United States
Duration: Oct 26 2005Oct 29 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3749 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005
CountryUnited States
CityPalm Springs, CA
Period10/26/0510/29/05

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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