International Journal of Intelligent Information Systems
Volume 3, Issue 1, February 2014, Pages: 8-12
Received: Apr. 30, 2014;
Accepted: May 17, 2014;
Published: May 30, 2014
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Faten Faraj Abushmmala, Computer Science Engineering Department, Islamic University (IUG)，Gaza, Palestine
Fadwa Faraj Abushmmala, Industrial Engineering Department, Islamic University (IUG)，Gaza, Palestine
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%.
Faten Faraj Abushmmala,
Fadwa Faraj Abushmmala,
Processing Overlapped Cells Using K-Means and Watershed, International Journal of Intelligent Information Systems.
Vol. 3, No. 1,
2014, pp. 8-12.
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