A Divide and Conquer Algorithm for Electron Microscopy Segmentation

Abstract

Cryo-Electron Microscopy is a biophysical technique able to visualize macromolecular complexes by producing 3-dimensional images. Currently, it has been advanced to be the second popular technique to construct protein molecules in terms of the number of structures released annually. The main advantages of cryo-electron microscopy are its ability to visualize large molecules, molecules that are hard to crystalize in their native environment. One critical step to construct the structure of a molecule from cryo-electron microscopy is to divide the image into regions for the chains/subunits that make up the molecule/complex. If the image is accurately segmented into the correct regions, the process of modelling using existing tools become easier and faster. In this paper, we developed a divide-and-conquer algorithm to segment a given cryo-electron microscopy image efficiently. Our approach is based on the popular watershed algorithm. We tested our method on 10 authentic images and compared it with Segger. Although, it is difficult to conduct an accurate comparison, the results show that the performance of our algorithm is competitive when compared to Segger.