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An image analysis suite for spot detection and spot matching in two‐dimensional electrophoresis gels
Author(s) -
Srinark Thitiwan,
Kambhamettu Chandra
Publication year - 2008
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.200700244
Subject(s) - pattern recognition (psychology) , matching (statistics) , centroid , artificial intelligence , similarity (geometry) , computer science , spots , distance transform , segmentation , algorithm , image (mathematics) , mathematics , chemistry , statistics
We propose a suite of novel algorithms for image analysis of protein expression images obtained from 2‐D electrophoresis. These algorithms are a segmentation algorithm for protein spot identification, and an algorithm for matching protein spots from two corresponding images for differential expression study. The proposed segmentation algorithm employs the watershed transformation, k ‐means analysis, and distance transform to locate the centroids and to extract the regions of the proteins spots. The proposed spot matching algorithm is an integration of the hierarchical‐based and optimization‐based methods. The hierarchical method is first used to find corresponding pairs of protein spots satisfying the local cross‐correlation and overlapping constraints. The matching energy function based on local structure similarity, image similarity, and spatial constraints is then formulated and optimized. Our new algorithm suite has been extensively tested on synthetic and actual 2‐D gel images from various biological experiments, and in quantitative comparisons with ImageMaster2D Platinum™ the proposed algorithms exhibit better spot detection and spot matching.