Cell splitting using dynamic programming

Jose A. Rosado-Toro, Jeffrey J. Rodriguez

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

2 Scopus citations

Abstract

Cell detection and segmentation is an essential step in many biological studies. Unfortunately, automatic splitting of merged cells continues to be one of the most challenging problems. We present an algorithm for splitting two adjacent cells using geometric analysis as well as a dynamic programming approach to find the optimum path. The algorithm is compared with Al-Kohafi's algorithm, which uses a graph-cut method to split the merged cells, and Dzyubachyk's algorithm which uses a three dimensional Radon transform. The performance was analyzed using images from Dzyubachyk's dataset. The results show a mean improvement of 27.2% versus the other two methods.

Original languageEnglish (US)
Title of host publication2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012, Proceedings
Pages33-36
Number of pages4
DOIs
StatePublished - Jul 2 2012
Event2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012 - Santa Fe, NM, United States
Duration: Apr 22 2012Apr 24 2012

Publication series

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation

Other

Other2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012
CountryUnited States
CitySanta Fe, NM
Period4/22/124/24/12

Keywords

  • Segmentation
  • cell splitting
  • dynamic programing

ASJC Scopus subject areas

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

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  • Cite this

    Rosado-Toro, J. A., & Rodriguez, J. J. (2012). Cell splitting using dynamic programming. In 2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012, Proceedings (pp. 33-36). [6202446] (Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation). https://doi.org/10.1109/SSIAI.2012.6202446