CT Image Segmentation Based on clustering Methods.

Authors

  • Rand K. Mohammed Medical Engineering, College of Medicine, Diyala University.
  • Asmaa A. Ajwad Medical Engineering, College of Medicine, Diyala University.

DOI:

https://doi.org/10.32007/jfacmedbagdad.5221033

Keywords:

CT, Image Segmentation, k-mean Clustering, Median Filtering.

Abstract

Background: image processing of medical images is major method to increase reliability of cancer diagnosis.
Methods: The proposed system proceeded into two stages: First, enhancement stage which was performed using of median filter to reduce the noise and artifacts that present in a CT image of a human lung with a cancer, Second: implementation of k-means clustering algorithm.
Results: the result image of k-means algorithm compared with the image resulted from implementation of fuzzy c-means (FCM) algorithm.
Conclusion: We found that the time required for k-means algorithm implementation is less than that of FCM algorithm.MATLAB package (version 7.3) was used in writing the programming code of our work.

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Published

2010-07-04

How to Cite

1.
CT Image Segmentation Based on clustering Methods. JFacMedBagdad [Internet]. 2010 Jul. 4 [cited 2024 Mar. 28];52(2):232-6. Available from: https://iqjmc.uobaghdad.edu.iq/index.php/19JFacMedBaghdad36/article/view/1033

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