Shape based identification of proteins in volume images

Abstract

A template based matching method, adopted to the application of identifying individual proteins of a certain kind in volume images, is presented. Grey-level and gradient magnitude information is combined in the watershed algorithm to extract stable borders. These are used in a subsequent hierarchical matching algorithm. The matching algorithm uses a distance transform to search for local best fits between the edges of a template and edges in the underlying image. It is embedded in a resolution pyramid to decrease the risk of getting stuck in false local minima. This method makes it possible to find proteins attached to other proteins, or proteins appearing as split into parts in the images. It also decreases the amount of human interaction needed for identifying individual proteins of the searched kind. The method is demonstrated on a set of three volume images of the antibody IgG in solution. © Springer-Verlag Berlin Heidelberg 2005.