2D-gel spot detection and segmentation based on modified image-aware grow-cut and regional intensity information. Issue 1 (October 2015)

• Record Type: Journal Article
• Authors: Kostopoulou, E.; Katsigiannis, S.; Maroulis, D.
• Is Part Of: Computer methods and programs in biomedicine. Volume 122:Issue 1(2015)
• Page Start: 26
• Page End: 39
• Publication Date: 2015-10
• Subjects: Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2015.06.007
• Languages: English
• ISSNs: 0169-2607

Abstract

<abstract abstract-type="author-highlights" id="abs0005"> <title id="sect0005">Highlights</title> <sec> <p id="spar0005"> <list id="lis0005"> <list-item id="lsti0005"> <label></label> <p id="par0005">A novel approach for 2D-gel image spot detection and segmentation.</p> </list-item> <list-item id="lsti0010"> <label></label> <p id="par0010">The segmentation process includes a grow-cut approach with a custom update rule that takes into consideration the inherent characteristics of 2D-gel images.</p> </list-item> <list-item id="lsti0015"> <label></label> <p id="par0015">Real and synthetic 2D-gel images containing a total of more than 20, 000 protein spots are used for qualitative and quantitative evaluation.</p> </list-item> <list-item id="lsti0020"> <label></label> <p id="par0020">Better detection and segmentation performance than state-of-the-art methods.</p> </list-item> </list> </p> </sec> </abstract>