Segmentation and classification of 3-D spots in FISH images

Sundaresh Ram, Jeffrey J. Rodriguez, Giovanni Bosco

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

3 Scopus citations

Abstract

In this paper, we propose an automated method to segment and classify the 3-D spots in fluorescence in-situ hybridization images from ovarian germline nurse cells of Drosophila melanogaster. The spot segmentation consists of a smoothing step followed by top-hat filtering and 3-D region growing. After the spots are segmented, a number of features such as volume, texture, and contrast are measured so as to classify the real spots from the noise with the help of a Bayesian classifier. Experimental results demonstrate the effectiveness of the proposed scheme in terms of segmentation and classification accuracy.

Original languageEnglish (US)
Title of host publication2010 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2010 - Proceedings
Pages101-104
Number of pages4
DOIs
StatePublished - 2010
Event2010 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2010 - Austin, TX, United States
Duration: May 23 2010May 25 2010

Publication series

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation

Other

Other2010 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2010
Country/TerritoryUnited States
CityAustin, TX
Period5/23/105/25/10

Keywords

  • Anisotropic diffusion
  • FISH images
  • ROC analysis
  • Segmentation
  • Spot detection
  • Top-hat filtering

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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