3 research outputs found
Local Pixel Value Collection Algorithm for Spot Segmentation in Two-Dimensional Gel Electrophoresis Research
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