Local Pixel Value Collection Algorithm for Spot Segmentation in Two-Dimensional Gel Electrophoresis Research

Abstract

Two-dimensional gel-electrophoresis (2-DE) images show the expression levels of several hundreds of proteins where each protein is represented as a blob-shaped spot of grey level values. The spot detection, that is, the segmentation process has to be efficient as it is the first step in the gel processing. Such extraction of information is a very complex task. In this paper, we propose a novel spot detector that is basically a morphology-based method with the use of a seeded region growing as a central paradigm and which relies on the spot correlation information. The method is tested on our synthetic as well as on real gels with human samples from SWISS-2DPAGE (two-dimensional polyacrylamide gel electrophoresis) database. A comparison of results is done with a method called pixel value collection (PVC). Since our algorithm efficiently uses local spot information, segments the spot by collecting pixel values and its affinity with PVC, we named it local pixel value collection (LPVC). The results show that LPVC achieves similar segmentation results as PVC, but is much faster than PVC.

Impulse noise removal in two-dimensional electrophoresis images based on dome recognition

“…The denoising methods previously applied in 2DE images could be divided into four classes [1] [2]: linear filters, adaptive filters [2] [3], nonlinear filters [3] [4] and spatial-frequency domain filters [5] [6]. In common sense, impulse noise means salt-and-pepper noise and random-valued noise.…”

A Laplacian of Gaussian-Based Approach for Spot Detection in Two-Dimensional Gel Electrophoresis Images

“…The two-dimensional gel electrophoresis (2-DE) images show the expression levels of several hundreds of proteins where each protein is represented as a spot of grey level values [2]. In order to extract protein spots, image processing techniques can help us to analyze proteins further.…”

“…The watershed transformation algorithm has also been a popular choice for 2-DE image segmentation [3] [5]. State of the art approaches to spot detection by image segmentation include geometric algorithms [6], parametric spot models [3] and the pixel value collection method [2] [7].…”

A Computer-Based Technique for Automated Spot Detection in Proteomics Images

“…Morphological operations are capable of preserving topological properties such as connectivity and homotopy, whereas they are suitable for detecting the location of geometric characteristics, such as intensity peaks [10]- [14]. They have been successfully applied on various biomedical domains, including electron micrographs of muscle cross sections [15], gastric tumor pathologic cell images [16], digital color eye fundus images [17] as well as on 2-D PAGE imaging [18], [19]. This paper introduces a novel computer-based technique for automated detection of protein spots in 2-D PAGE images.…”