Performance analysis of medical microscopic image segmentation techniques


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Volume :

10

Issue :

1

Abstract :

Segmentation techniques play an important role in medical image analysis. More research is required to understand the performance of various segmentation techniques on microscopic medical images. In this paper, four segmentation techniques are analyzed to segment the chromosome images. Performance metrics like SSIM, MSSIM are evaluated for Fuzzy C-Means of clustering, K-Means clustering, Kernel weighted Fuzzy C-Means (KWFCM) and Watershed segmentation. These techniques are compared subjectively and objectively. KWFCM is found to be good and suitable for segmentation of chromosomes from the simulation results.

Keyword :

FCM, K-Means, KWFCM, Watershed.
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