Automated 3D Visualization of Electron Microscope Tomograms

Abstract

In this paper, we propose a 3D visualization method for ultra-high voltage electron microscope tomography intended for use with biological samples. The most important process for constructing 3D images from UHVTEM tomograms is the extraction of contours from 2D sliced images. However, automatic extraction of contours is difficult because of typical noise and artifacts. The proposed method automatically extracts contours by the 3D level set method. In general, the result of the extraction with the level set method depends on the definition of initial contours and parameters. These parameters are usually set manually. Our method automatically generates the initial contours and decides the fittest parameters for the level set method. We verify the effectiveness of our method by applying the technique to two types of unicellular organisms, to compare the results of the proposed method with manual extraction. The automated method successfully identified most cell tissues, with the exception of a limitation in the imaging of tubular-shaped cell structures.