Institute for Critical Technology and Applied Science, Virginia Tech, Blacksburg, VA 24061, USA.
Microsc Microanal. 2012 Dec;18(6):1362-7. doi: 10.1017/S1431927612013530. Epub 2012 Dec 5.
In this article, we demonstrate the application of a new compressed sensing three-dimensional reconstruction algorithm for electron tomography that increases the accuracy of morphological characterization of nanostructured materials such as nanocrystalline iron oxide particles. A powerful feature of the algorithm is an anisotropic total variation norm for the L1 minimization during algebraic reconstruction that effectively reduces the elongation artifacts caused by limited angle sampling during electron tomography. The algorithm provides faithful morphologies that have not been feasible with existing techniques.
本文展示了一种新的压缩感知三维重建算法在电子断层扫描中的应用，该算法提高了纳米结构材料（如纳米晶氧化铁颗粒）的形态特征描述的准确性。该算法的一个强大功能是在代数重建过程中对 L1 最小化使用各向异性全变差范数，有效地减少了由于电子断层扫描中角度采样有限而导致的伸长伪影。该算法提供了真实的形态，这是现有技术所无法实现的。
