CRF-driven multi-compartment geometric model

S. Farhand, F. M. Andreopoulos, G. Tsechpenakis

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

Abstract

We present a hybrid framework for segmenting structures consisting of distinct inter-connected parts. We combine the robustness of Conditional Random Fields in appearance classification with the shape constraints of geometric models and the relative part topology constraints that multi-compartment modeling provides. We demonstrate the performance of our method in cell segmentation from fluorescent microscopic images, where the compartments of interest are the cell nucleus, cytoplasm, and the negative hypothesis (background). We compare our results with the most relevant model- and appearance-based segmentation methods.

Original languageEnglish (US)
Title of host publicationISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro
Pages1094-1097
Number of pages4
DOIs
StatePublished - Aug 22 2013
Event2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 - San Francisco, CA, United States
Duration: Apr 7 2013Apr 11 2013

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
CountryUnited States
CitySan Francisco, CA
Period4/7/134/11/13

Keywords

  • Cell segmentation
  • conditional random fields
  • deformable models
  • multi-compartment segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Farhand, S., Andreopoulos, F. M., & Tsechpenakis, G. (2013). CRF-driven multi-compartment geometric model. In ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro (pp. 1094-1097). [6556669] (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2013.6556669