Title :
Fast Automatic Segmentation of Nuclei in Microscopy Images of Tissue Sections
Author :
Laurain, V. ; Ramoser, H. ; Nowak, C. ; Steiner, G.E. ; Ecker, R.
Author_Institution :
Advanced Comput. Vision GmbH, Vienna
Abstract :
In this paper, we present a segmentation method for nuclei in microscopy images of tissue sections. The proposed method is completely automatic and performs well in the conflicting aims of speed efficiency, detection accuracy and shape fitting. It proposes an efficient alternative to existing methods, in achieving the three main usual segmentation steps: (i) background extraction, (ii) seed finding and (iii) seed growing. Eventually, some significant results are depicted and discussed
Keywords :
biological tissues; biomedical optical imaging; image segmentation; medical image processing; optical microscopy; background extraction; detection accuracy; fast automatic segmentation; microscopy images; nuclei; seed finding; seed growing; shape fitting; speed efficiency; tissue sections; Clustering algorithms; Computer vision; Data mining; Fluorescence; Histograms; Image segmentation; Microscopy; Pixel; Robustness; Working environment noise; Nuclei; microscopy images; segmentation;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1617199
