Segmentation of Marrow Cells Images Based on Fuzzy C-Means Clustering

Abstract:

When a person watches different marrow-cell images he or she can identify every type of cells easily. In this process, human’s visual system has ability to adapt the different shades of the color marrow cells images. We propose a segmentation method for marrow-cell images based on fuzzy c-means clustering (FCM). Firstly, the count of cluster is calculated out using the shades of the R-matrix of a RGB formatted marrow cells image. Secondly, the fuzzy c-means clustering method is done on the R-matrix. Finally, the pixel of G-matrix and B-matrix are divided into some clusters by “one to one correspondence” of the position of pixels that belong to R-matrix, G-matrix or B-matrix. This paper’s contribution could be summarized into three points: 1) a frame work of the fuzzy c-means clustering for marrow-cell images segmentation is proposed. 2) Using FCM and the R- matrix component of a RGB formatted marrow-cell images to generate the count of clustering. 3) This method could adaption different shades of different marrow-cell images.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 2160-2163
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.2160
• Online since: December 2012
• Authors: Guo Qiang Ma, Xiao Juan Wang
• Keywords: Fuzzy C-Mean Clustering, Marrow-Cell Images, Segmentation

References

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