Three-dimensional electron microscopy (3D EM) is a powerful technique for imaging complex biological macromolecules in order to further the understanding of their functions. It is achieving high goals and exceeding expectations unthinkable only a few years ago. However, there are still some problem areas where either not enough work has been invested or the work has not as yet been fruitful. A multidisciplinary approach is proposed to shed light on three of these areas by the application of image processing techniques: (i) Incorporation of realistic image formation models into new reconstruction algorithms which take into account image blurring models of the aberrations of the electron microscope and which are at the same time noise-resistant and flexible with respect to the different data collection geometries. (ii) Incorporation of knowledge regarding the specimen obtained by means other than EM, such as high resolution surface relief information and information regarding the chemical nature of the specimen. (iii) Improvement of the rendering and the analysis of the reconstructed volumes by the development of more accurate segmentation (of the specimen from its background) and visualization algorithms. These basic aims are to be complemented by a rigorous approach to validating claims of superiority of any of the newly developed methods over those used in current practice. The approach will include very realistic simulations of the electron microscopic imaging process on structures in the Protein Data Bank. Image processing methodology for obtaining more accurate structural information by 3D EM than what can be achieved by current techniques will contribute to our understanding of the detailed molecular mechanisms of some of the key cell functions and, consequently, impact on the field of drug discovery. The proposed work is relevant to cardiovascular and pulmonary disease and health and to blood research.
NIH ExPorter
NIH ExPorter