DocumentCode :
3114316
Title :
Adaptive marker-based watershed segmentation approach for T cell fluorescence images
Author :
Ge Fan ; Jian-Wei Zhang ; Yong Wu ; Dong-Fa Gao
Author_Institution :
Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Volume :
02
fYear :
2013
fDate :
14-17 July 2013
Firstpage :
877
Lastpage :
883
Abstract :
It is intractable problem to segment the fluorescence image of T-cells with different sizes, irregular shape, and severe overlapping by conventional marker-based watershed segmentation. In this paper, Adaptive Marker-controlled Watershed method (AMWS) will be proposed. The Otsu strategy firstly is performed twice in a row to capture as many T-cells as possible. Then based on T-cells´ roundish shape, an improved strategy to obtain markers adaptively is present using the evaluation of the segmentation result. This strategy is able to mark the single cell and the overlapping cells accurately. It avoids the ineffectiveness of ultimate erosion which is due to different sizes of cells. The experimental results show that the proposed strategy in this paper can effectively avoid over-segmentation and under-segmentation thus improves both accuracy and robustness of the segmentation.
Keywords :
cellular biophysics; erosion; fluorescence; image segmentation; AMWS; Otsu strategy; T cell fluorescence images; T-cells roundish shape; adaptive marker-based watershed segmentation; adaptive marker-controlled watershed method; overlapping cells; single cell; ultimate erosion; Abstracts; Image reconstruction; Image segmentation; Distance reconstruction; Marker-based watershed; T cell fluorescence image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
Conference_Location :
Tianjin
Type :
conf
DOI :
10.1109/ICMLC.2013.6890407
Filename :
6890407
Link To Document :
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