Quantitative self-organizing maps for clustering electron tomograms.

Tomography emerges as a powerful methodology for determining the complex architectures of biological specimens that are better regarded from the structural point of view as singular entities. However, once the structure of a sufficiently large number of singular specimens is solved, quite possibly structural patterns start to emerge. This latter situation is addressed here, where the clustering of a set of 3D reconstructions using a novel quantitative approach is presented. In general terms, we propose a new variant of a self-organizing neural network for the unsupervised classification of 3D reconstructions. The novelty of the algorithm lies in its rigorous mathematical formulation that, starting from a large set of noisy input data, finds a set of "representative" items, organized onto an ordered output map, such that the probability density of this set of representative items resembles at its possible best the probability density of the input data. In this study, we evaluate the feasibility of application of the proposed neural approach to the problem of identifying similar 3D motifs within tomograms of insect flight muscle. Our experimental results prove that this technique is suitable for this type of problem, providing the electron microscopy community with a new tool for exploring large sets of tomogram data to find complex patterns.

A new phase consistency criterion and its application in electron crystallography

In this work, we present the principles and potential advantages of a methodology to assess Fourier components in terms of phase consistency. We define a new phase consistency criterion among sets of spatially translated images based upon a novel conception of the spatial shift property of the Fourier transform. The article shows how this criterion can be used in the alignment stage of the 3D reconstruction process with a two-fold objective: Assessment of the frequency components and robustness in the alignment. In that sense, the article shows and analyzes the results obtained from the application of the new index of quality in the context of projection image alignment. We have focussed our attention on the electron crystallography field, by applying such a phase consistency definition over image reflections. The results that have been obtained show that the new phase-consistency definition may complement the traditional SNR-based index of quality (commonly known as IQ) of reflections. As a consequence, the reliability of the alignment may be improved by discarding those reflections judged as non-reliable according to the phase-consistency criterion.

Xmipp: An Image Processing Package for Electron Microscopy

We present in this article a specialized suite of image processing programs primarily aimed at obtaining the three-dimensional reconstruction of biological specimens from large sets of projection images obtained by transmission electron microscopy. The programs are written in ANSI-C and use X-Windows for graphical output. A number of parallel extensions using PVM and PARMACS are provided. The programs are freely available by anonymous ftp at ftp.cnb.uam.es.