Fuzzy watershed segmentation algorithm: an enhanced algorithm for 2D gel electrophoresis image segmentation
by Shaheera Rashwan; Amany Sarhan; Muhamed Talaat Faheem; Bayumy A. Youssef
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 12, No. 3, 2015

Abstract: Detection and quantification of protein spots is an important issue in the analysis of two-dimensional electrophoresis images. However, there is a main challenge in the segmentation of 2DGE images which is to separate overlapping protein spots correctly and to find the weak protein spots. In this paper, we describe a new robust technique to segment and model the different spots present in the gels. The watershed segmentation algorithm is modified to handle the problem of over-segmentation by initially partitioning the image to mosaic regions using the composition of fuzzy relations. The experimental results showed the effectiveness of the proposed algorithm to overcome the over segmentation problem associated with the available algorithm. We also use a wavelet denoising function to enhance the quality of the segmented image. The results of using a denoising function before the proposed fuzzy watershed segmentation algorithm is promising as they are better than those without denoising.

Online publication date: Fri, 29-May-2015

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