DocumentCode :
457502
Title :
Classification of Segmented Regions in Brightfield Microscope Images
Author :
Tscherepanow, Marko ; Zöllner, Frank ; Kummert, Franz
Author_Institution :
Appl. Comput. Sci., Bielefeld Univ.
Volume :
3
fYear :
0
fDate :
0-0 0
Firstpage :
972
Lastpage :
975
Abstract :
The subcellular localisation of proteins in living cells is an important step to determine their function. A common method is the evaluation of fluorescence images. The position of marked proteins, visible as bright spots, enables conclusions concerning their function. In order to determine the subcellular localisation, it is crucial to know the exact positions of the considered cells within an image. These are provided by the segmentation of a corresponding brightfield microscope image. As the resulting segments do not exclusively comprise cells, they have to be classified. Therefore, we propose an approach for the classification of the resulting segments in ´cells´ and ´non-cells´, which is an essential step of the automatic recognition of cells and thus of the automatic subcellular localisation of proteins in living cells
Keywords :
cellular biophysics; image classification; image segmentation; medical image processing; proteins; automatic recognition; automatic subcellular localisation; brightfield microscope images; fluorescence images; living cells; proteins; segmented regions; Active contours; Biomembranes; Cells (biology); Computer science; Fluorescence; Genomics; Image segmentation; Microscopy; Pixel; Proteins;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
ISSN :
1051-4651
Print_ISBN :
0-7695-2521-0
Type :
conf
DOI :
10.1109/ICPR.2006.369
Filename :
1699688
Link To Document :
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