Analysis of 2D-gel images for detection of protein spots using a novel non-separable wavelet based method

• A 2D gel image is modeled using the inter-scale ratio of wavelet coefficients.
• The image is divided into three distinct parts: spot regions, edges and background.
• A single threshold is enough to extract the protein spots from the 2D gel image.
• The proposed method provides more accurate segmentation than available methods.

2D-gel electrophoresis (2DGE) is an important technique in proteomics for analyzing the protein expressions. However, the analysis of 2DGE images is still a cumbersome and tedious task. One of the main reasons is the presence of a large amount of the inhomogeneities in the foreground and the background intensities. In this paper, we have proposed a novel approach of segmentation of the protein spots in the non separable wavelet domain. It utilizes the inter-scale relationship among enhanced wavelet coefficients, which can easily distinguish the different features of the image—the interior region of spots, the edges and the background. This technique is based on a single threshold and is independent of the gray value of the image. It copes with the inhomogeneities in the 2DGE images up to a great extent, which is helpful for finding the protein spots accurately. The artifacts are further removed using a non-threshold based method comprising a weighted Gaussian energy distribution model. Experimental results show that our method outperforms the available commercial software and previously reported works.

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