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

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...

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Detalles Bibliográficos
Autores principales: Pal, U., Rodenacker, Karsten, Chaudhuri, B. B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 1998
Materias:
Other
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4612250/
https://www.ncbi.nlm.nih.gov/pubmed/10391376
http://dx.doi.org/10.1155/1998/235029
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author Pal, U.
Rodenacker, Karsten
Chaudhuri, B. B.
author_facet Pal, U.
Rodenacker, Karsten
Chaudhuri, B. B.
author_sort Pal, U.
collection PubMed
description 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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spelling pubmed-46122502016-01-12 Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points Pal, U. Rodenacker, Karsten Chaudhuri, B. B. Anal Cell Pathol Other 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%. IOS Press 1998 1998-01-01 /pmc/articles/PMC4612250/ /pubmed/10391376 http://dx.doi.org/10.1155/1998/235029 Text en Copyright © 1998 Hindawi Publishing Corporation.
spellingShingle Other
Pal, U.
Rodenacker, Karsten
Chaudhuri, B. B.
Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points
title Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points
title_full Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points
title_fullStr Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points
title_full_unstemmed Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points
title_short Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points
title_sort automatic cell segmentation in cyto- and histometry using dominant contour feature points
topic Other
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4612250/
https://www.ncbi.nlm.nih.gov/pubmed/10391376
http://dx.doi.org/10.1155/1998/235029
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AT rodenackerkarsten automaticcellsegmentationincytoandhistometryusingdominantcontourfeaturepoints
AT chaudhuribb automaticcellsegmentationincytoandhistometryusingdominantcontourfeaturepoints

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