Title :
Cell nuclei segmentation using fuzzy logic engine
Author :
Begelrnan, G. ; Gur, Eran ; Rivli, Ehud ; Rudzsky, Michnel ; Zalevsky, Zeev
Author_Institution :
Dept. of Comput. Sci., Israel Inst. of Technol., Haifa, Israel
Abstract :
The task of segmenting cell nuclei in microscope images is a classical image analysis 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.
Keywords :
biology computing; fuzzy logic; image segmentation; microscopes; nucleus; cell nuclei segmentation; fuzzy logic engine; image analysis problem; microscope image; pathology detection; semi-supervised training; Computer science; Data mining; Engines; Fuzzy logic; Fuzzy sets; Image analysis; Image color analysis; Image segmentation; Pathology; Transmission electron microscopy;
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
Print_ISBN :
0-7803-8554-3
DOI :
10.1109/ICIP.2004.1421728
