A Hierarchical Watershed Transformation Based On A-Priori Information For The Spot Detection In 2-D Gel Electrophoresis Images

For the spot detection in 2-D electrophoresis images an approach which is based on the combination of the watershed transformation (WST) with a-priori knowledge is presented. To identify spot regions in the over segmented result of the WST two types of regions have to be found: Regions that correspond to a complete spot and regions that cover only a part of a spot. The first localization step, the gray value analysis, is based on the assumptions that spot regions have significantly higher gray values than the background and that they border on a background region. Since not all remaining regions are spot or partial spot regions, additionally a curvature analysis is done. Here the a-priori knowledge is used that regarding a gel image as a surface, the shape of a spot is obviously convex. Consequently, considering the second derivative all required spot and partial spot regions can be obtained by the regions of convex curvature. In a final merging step all partial spot regions covering one spot have to be combined to only one spot region. As merging criterion two spot characteristics are used. A spot should have an approximately elliptical shape and partial spot regions of one spot should have a local convex curvature in a small neighborhood along their boundary.