Premium
A fast spot segmentation algorithm for two‐dimensional gel electrophoresis analysis
Author(s) -
Wu Yecheng,
Lemkin Peter F.,
Upton Kyle
Publication year - 1993
Publication title -
electrophoresis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.666
H-Index - 158
eISSN - 1522-2683
pISSN - 0173-0835
DOI - 10.1002/elps.11501401208
Subject(s) - raster graphics , computer science , spots , segmentation , computation , algorithm , raster scan , automation , image (mathematics) , two dimensional gel electrophoresis , artificial intelligence , hot spot (computer programming) , image segmentation , pattern recognition (psychology) , chemistry , engineering , mechanical engineering , biochemistry , proteomics , gene , operating system
An important issue in the automation of two‐dimensional gel electrophoresis image analysis is the detection and quantification of protein spots. A spot segmentation algorithm must detect, define the extent of, and measure the integrated density of spots under a wide variety of actual gel image conditions. Besides these functions, the algorithm must be memory efficient to be able to process very large gel images and do this in a reasonable amount of computation time on low‐cost computers, such as workstations and personal computers. We have developed a fast spot segmentation algorithm, extending the GELLAB‐II segmenter, which extracts spots in a single raster scanning pass through the gel image. The performance analysis of the algorithm will be given in the paper as well as a discussion of the algorithm.