Feature modeling and tomographic reconstruction of electron microscopy images

Abstract

This work introduces a combination of image processing and analysis methods that perform feature extraction, shape analysis and tomographic reconstruction of Electron Microscopy images. These have been implemented on images of the AIDS virus interacting with neutralizing molecules. The AIDS virus spike is the primary target of drug design as it is directly involved in infecting host cells. First, a fully automated technique is introduced that can extract sub-volumes of the AIDS virus spike and be used to build a statistical model without the need for any user supervision. Such an automatic feature extraction method can significantly enhance the overall process of shape analysis of the AIDS virus spike imaged through the electron microscope. Accurate models of the virus spike will help in the development of better drug design strategies. Secondly, a tomographic reconstruction method implemented using a shape based regularization technique is introduced. Spatial models of known features in the structure being reconstructed are integrated into the reconstruction process as regularizers. This regularization scheme is driven locally through shape information obtained from segmentation and compared with a known spatial model. This method shows reduced blurring, and an improvement in the resolution of the reconstructed volume was also measured. It performs better than popular current techniques and can be extended to other tomographic modalities. Improved Electron Tomography reconstructions will provide better structure elucidation and improved feature visualization, which can aid in solving key biological issues.