Using grey-level and shape information for decomposing proteins in 3D images

An image analysis method for decomposing 3D objects using a combination of grey-level and shape is presented. The method consists of two major parts: seeding based on grey-level information and growth from the seeds based on shape information. The growth is performed in two steps in order to prevent seeds located in peripheral or protruding parts of the object from growing into other parts. The method was developed to decompose 3D reconstructions of proteins into their structural subunits. The proteins are imaged with SET (Sidec electron tomography) at a resolution of approximately 2 nm. Decomposition can be a useful tool in the segmentation process to help distinguish between true protein molecules and other objects. It can also be useful for analyzing and visualizing interactions between proteins.