A Laplacian of Gaussian-Based Approach for Spot Detection in Two-Dimensional Gel Electrophoresis Images
Two-dimension gel electrophoresis (2-DE) is a proteomic technique that allows the analysis of protein profiles expressed in a given cell, tissue or biological system at a given time. The 2-DE images depict protein as spots of various intensities and sizes. Due to the presence of noise, the inhomogeneous background, and the overlap between the spots in 2-DE image, the protein spot detection is not a straightforward process. In this paper, we present an improved protein spot detection approach, which is based on Laplacian of Gaussian algorithm, and we extract the regional maxima by morphological grayscale reconstruction algorithm, which can reduce the impact of noisy and background in spot detection. Experiments on real 2-DE images show that the proposed approach is more reliable, precise and less sensitive to noise than the traditional Laplacian of Gaussian algorithm and it offers a good performance in our gel image analysis software.
Two-dimensional gel electrophoresis Spot detection Laplacian of Gaussian Morphological grayscale reconstruction
Feng He Bangshu Xiong Chengli Sun Xiaobin Xia
Key Laboratory of Nondestructive Test of Ministry of Education,Nanchang Hangkong University, 330063 Nanchang, P.R. China
国际会议
南昌
英文
8-15
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）