|About this Abstract
||2014 TMS Annual Meeting & Exhibition
||Data Analytics for Materials Science and Manufacturing
||Model-based Iterative Reconstruction for Multimodal Electron Tomography
||Lawrence Drummy, Singanallur Venkatakrishnan, Marc DeGraef, Jeff Simmons, Charles Bouman
|On-Site Speaker (Planned)
Electron tomography (ET) is a powerful tool for reconstruction of the 3D structure of materials to sub-nanometer resolution. Significant advances in ET instrumentation have been made in recent years, yet current reconstruction algorithms for inversion of the projection data do not properly model the image formation process and therefore yield poor results. Model Based Iterative Reconstruction (MBIR) provides a framework for tomographic reconstruction that incorporates a model for data acquisition and a model for the object to obtain reconstructions that are qualitatively superior to current methods such as Filtered Back Projection (FBP) and quantitatively accurate. Here we present a novel MBIR algorithm for multi-modal ET which accounts for the presence of anomalous measurements from Bragg scatter in the Bright Field (BF) data. MBIR results on simulated as well as real data show that the method can dramatically improve reconstructions of High Angle Annular Dark Field and BF-ET compared to FBP.
||Planned: A print-only volume