DocumentCode :
705310
Title :
Segmentation of cell nuclei from histological images by ellipse fitting
Author :
Hukkanen, J. ; Hategan, A. ; Sabo, E. ; Tabus, I.
Author_Institution :
Dept. of Signal Process., Tampere Univ. of Technol., Tampere, Finland
fYear :
2010
fDate :
23-27 Aug. 2010
Firstpage :
1219
Lastpage :
1223
Abstract :
We propose a new algorithm for non-assisted segmentation of possibly clustered nuclei from histological images. We use elliptic shapes as parametric models to represent the nuclei contours and fit the parameters using the information present in the gray level intensity image and in the derived gradient image. Multiple seeds for each closed contour are found by ultimate erosion of an estimated edge image, resulting in an number of seeds generally larger than the number of nuclei. Our algorithm, called segmentation of nuclei by ellipse fitting (SNEF), constructs several candidate contours for each seed by fitting ellipses to selected subsets of edge pixels. In the end the algorithm selects the contours to be declared nuclei by comparing the values of a suitably chosen goodness of fit criterion. The proposed algorithm produces segmentations in agreement with an expert pathologist.
Keywords :
biological tissues; image colour analysis; image segmentation; medical image processing; pattern clustering; SNEF; cell nuclei segmentation; edge image estimation; ellipse fitting; gradient imaging; gray level intensity imaging; histological imaging; multiple seed; nonassisted segmentation algorithm; parametric model; segmentation of nuclei by ellipse fitting; ultimate erosion; Clustering algorithms; Image edge detection; Image segmentation; Object segmentation; Shape; Signal processing algorithms; Silicon;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2010 18th European
Conference_Location :
Aalborg
ISSN :
2219-5491
Type :
conf
Filename :
7096583
Link To Document :
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