Cell Nuclei Segmentation Using Fuzzy Logic Engine
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Cell nuclei segmentation using fuzzy logic engine.
In ICIP04, V: 2937-2940, 2004
Online Version
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Abstract
The task of segmenting cell nuclei in microscope is a classical image analyses problem. The accurate nuclei segmentation may contribute to development of successful system which automate the analysis of microscope images for pathology detection. In this article we describe a method for semi-supervised training of fuzzy logic engine. The fuzzy logic engine is applied to connect a set of parameters proven to be important for nucleus segmentation. In addition each parameter for itself is detected using a set of fuzzy logic rules. We present results of nuclei segmentation using fuzzy logic set of rules.
Co-authors
Bibtex Entry
@inproceedings{BegelmanGRRZ04i,
title = {Cell nuclei segmentation using fuzzy logic engine},
author = {Grigory Begelman and Eran Gur and Ehud Rivlin and Michael Rudzsky and Zeev Zalevsky},
year = {2004},
booktitle = {ICIP04},
pages = {V: 2937-2940},
abstract = {The task of segmenting cell nuclei in microscope is a classical image analyses problem. The accurate nuclei segmentation may contribute to development of successful system which automate the analysis of microscope images for pathology detection. In this article we describe a method for semi-supervised training of fuzzy logic engine. The fuzzy logic engine is applied to connect a set of parameters proven to be important for nucleus segmentation. In addition each parameter for itself is detected using a set of fuzzy logic rules. We present results of nuclei segmentation using fuzzy logic set of rules.}
}