CT Image Segmentation Based on clustering Methods.

المؤلفون

  • 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

الكلمات المفتاحية:

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

الملخص

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.

التنزيلات

تنزيل البيانات ليس متاحًا بعد.

منشور

2010-07-04

كيفية الاقتباس

1.
Mohammed RK, Ajwad AA. CT Image Segmentation Based on clustering Methods. J Fac Med Baghdad [انترنت]. 4 يوليو، 2010 [وثق 22 نوفمبر، 2024];52(2):232-6. موجود في: https://iqjmc.uobaghdad.edu.iq/index.php/19JFacMedBaghdad36/article/view/1033

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