Processing Overlapped Cells Using K-Means and Watershed

Faten Faraj Abushmmala; Fadwa Faraj Abushmmala

doi:doi:10.11648/j.ijiis.20140301.12

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Processing Overlapped Cells Using K-Means and Watershed

Faten Faraj Abushmmala, Fadwa Faraj Abushmmala

Published in International Journal of Intelligent Information Systems (Volume 3, Issue 1)

Received: 30 April 2014 Accepted: 17 May 2014 Published: 30 May 2014

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Abstract

Processing overlapped cells are tricky process especially when an automatic computerized system deals with 2D images of cells needed to be processed in biomedical filed, if these cells are overlapped this might give the impression and wrong indication of abnormality presence. In this paper a methodology are suggested and implemented to separate the overlapped from non-overlapped cells giving as a result two groups (clusters) for each. And we try to give an estimation of numbers of cells that overlapped under the microscope, the success rates of separating the two clusters (overlapped and non overlapped cells) are 100% while the success rate of the estimating the number of correct cells that overlapped compared with medical personal point view are 79.3%.

Published in	International Journal of Intelligent Information Systems (Volume 3, Issue 1)
DOI	10.11648/j.ijiis.20140301.12
Page(s)	8-12
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Image Processing, K-Means, Blood Cells, Clustering, Watershed

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APA Style

Faten Faraj Abushmmala, Fadwa Faraj Abushmmala. (2014). Processing Overlapped Cells Using K-Means and Watershed. International Journal of Intelligent Information Systems, 3(1), 8-12. https://doi.org/10.11648/j.ijiis.20140301.12

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ACS Style

Faten Faraj Abushmmala; Fadwa Faraj Abushmmala. Processing Overlapped Cells Using K-Means and Watershed. Int. J. Intell. Inf. Syst. 2014, 3(1), 8-12. doi: 10.11648/j.ijiis.20140301.12

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AMA Style

Faten Faraj Abushmmala, Fadwa Faraj Abushmmala. Processing Overlapped Cells Using K-Means and Watershed. Int J Intell Inf Syst. 2014;3(1):8-12. doi: 10.11648/j.ijiis.20140301.12

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@article{10.11648/j.ijiis.20140301.12,
  author = {Faten Faraj Abushmmala and Fadwa Faraj Abushmmala},
  title = {Processing Overlapped Cells Using K-Means and Watershed},
  journal = {International Journal of Intelligent Information Systems},
  volume = {3},
  number = {1},
  pages = {8-12},
  doi = {10.11648/j.ijiis.20140301.12},
  url = {https://doi.org/10.11648/j.ijiis.20140301.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20140301.12},
  abstract = {Processing overlapped cells are tricky process especially when an automatic computerized system deals with 2D images of cells needed to be processed in biomedical filed, if these cells are overlapped this might give the impression and wrong indication of abnormality presence. In this paper a methodology are suggested and  implemented to separate the overlapped from non-overlapped cells giving as a result two groups (clusters) for each. And we try to give an estimation of  numbers of cells that overlapped under the microscope, the success rates of separating the two clusters (overlapped and non overlapped cells) are 100% while the success rate of the estimating the number of correct cells that overlapped compared with medical personal point view are 79.3%.},
 year = {2014}
}

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TY  - JOUR
T1  - Processing Overlapped Cells Using K-Means and Watershed
AU  - Faten Faraj Abushmmala
AU  - Fadwa Faraj Abushmmala
Y1  - 2014/05/30
PY  - 2014
N1  - https://doi.org/10.11648/j.ijiis.20140301.12
DO  - 10.11648/j.ijiis.20140301.12
T2  - International Journal of Intelligent Information Systems
JF  - International Journal of Intelligent Information Systems
JO  - International Journal of Intelligent Information Systems
SP  - 8
EP  - 12
PB  - Science Publishing Group
SN  - 2328-7683
UR  - https://doi.org/10.11648/j.ijiis.20140301.12
AB  - Processing overlapped cells are tricky process especially when an automatic computerized system deals with 2D images of cells needed to be processed in biomedical filed, if these cells are overlapped this might give the impression and wrong indication of abnormality presence. In this paper a methodology are suggested and  implemented to separate the overlapped from non-overlapped cells giving as a result two groups (clusters) for each. And we try to give an estimation of  numbers of cells that overlapped under the microscope, the success rates of separating the two clusters (overlapped and non overlapped cells) are 100% while the success rate of the estimating the number of correct cells that overlapped compared with medical personal point view are 79.3%.
VL  - 3
IS  - 1
ER  -

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Author Information

Faten Faraj Abushmmala

Computer Science Engineering Department, Islamic University (IUG)，Gaza, Palestine
Fadwa Faraj Abushmmala

Industrial Engineering Department, Islamic University (IUG)，Gaza, Palestine

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APA Style

Faten Faraj Abushmmala, Fadwa Faraj Abushmmala. (2014). Processing Overlapped Cells Using K-Means and Watershed. International Journal of Intelligent Information Systems, 3(1), 8-12. https://doi.org/10.11648/j.ijiis.20140301.12

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ACS Style

Faten Faraj Abushmmala; Fadwa Faraj Abushmmala. Processing Overlapped Cells Using K-Means and Watershed. Int. J. Intell. Inf. Syst. 2014, 3(1), 8-12. doi: 10.11648/j.ijiis.20140301.12

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AMA Style

Faten Faraj Abushmmala, Fadwa Faraj Abushmmala. Processing Overlapped Cells Using K-Means and Watershed. Int J Intell Inf Syst. 2014;3(1):8-12. doi: 10.11648/j.ijiis.20140301.12

Copy | Download

@article{10.11648/j.ijiis.20140301.12,
  author = {Faten Faraj Abushmmala and Fadwa Faraj Abushmmala},
  title = {Processing Overlapped Cells Using K-Means and Watershed},
  journal = {International Journal of Intelligent Information Systems},
  volume = {3},
  number = {1},
  pages = {8-12},
  doi = {10.11648/j.ijiis.20140301.12},
  url = {https://doi.org/10.11648/j.ijiis.20140301.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20140301.12},
  abstract = {Processing overlapped cells are tricky process especially when an automatic computerized system deals with 2D images of cells needed to be processed in biomedical filed, if these cells are overlapped this might give the impression and wrong indication of abnormality presence. In this paper a methodology are suggested and  implemented to separate the overlapped from non-overlapped cells giving as a result two groups (clusters) for each. And we try to give an estimation of  numbers of cells that overlapped under the microscope, the success rates of separating the two clusters (overlapped and non overlapped cells) are 100% while the success rate of the estimating the number of correct cells that overlapped compared with medical personal point view are 79.3%.},
 year = {2014}
}

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TY  - JOUR
T1  - Processing Overlapped Cells Using K-Means and Watershed
AU  - Faten Faraj Abushmmala
AU  - Fadwa Faraj Abushmmala
Y1  - 2014/05/30
PY  - 2014
N1  - https://doi.org/10.11648/j.ijiis.20140301.12
DO  - 10.11648/j.ijiis.20140301.12
T2  - International Journal of Intelligent Information Systems
JF  - International Journal of Intelligent Information Systems
JO  - International Journal of Intelligent Information Systems
SP  - 8
EP  - 12
PB  - Science Publishing Group
SN  - 2328-7683
UR  - https://doi.org/10.11648/j.ijiis.20140301.12
AB  - Processing overlapped cells are tricky process especially when an automatic computerized system deals with 2D images of cells needed to be processed in biomedical filed, if these cells are overlapped this might give the impression and wrong indication of abnormality presence. In this paper a methodology are suggested and  implemented to separate the overlapped from non-overlapped cells giving as a result two groups (clusters) for each. And we try to give an estimation of  numbers of cells that overlapped under the microscope, the success rates of separating the two clusters (overlapped and non overlapped cells) are 100% while the success rate of the estimating the number of correct cells that overlapped compared with medical personal point view are 79.3%.
VL  - 3
IS  - 1
ER  -

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