Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points | Zendy

Umapada Pal | Zendy; Karsten Rodenacker | Zendy; B.B. Chaudhuri | Zendy

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Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points

Author(s) -

Umapada Pal,

Karsten Rodenacker,

B.B. Chaudhuri

Publication year - 1998

Publication title -

analytical cellular pathology

Language(s) - English

Resource type - Journals

eISSN - 2210-7185

pISSN - 2210-7177

DOI - 10.1155/1998/235029

Subject(s) - segmentation , feature (linguistics) , artificial intelligence , pattern recognition (psychology) , contour line , computer vision , computer science , active contour model , cluster analysis , image segmentation , cluster (spacecraft) , cartography , geography , philosophy , linguistics , programming language

Automatic cell segmentation has various application potentials in cytometry and histometry. In this paper, an automatic cluster (touching) cell segmentation approach using the dominant contour feature points has been presented. Dominant feature points are the locations of indentation on the contour of the cluster. First, dominant feature points on the contour of the cluster are detected by distance profile. Next, using shape features of the cells, these feature points are selected for segmentation. We compared the results of the proposed method with manual segmentation and observed that the method has an overall accuracy about to 82%.

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