Dictionary-Learning-Based Reconstruction Method for Electron Tomography

摘要

Electron tomography usually suffers from so called missing wedge artifactscaused by limited tilt angle range. An equally sloped tomography (EST)acquisition scheme (which should be called the linogram sampling scheme) wasrecently applied to achieve 2.4-angstrom resolution. On the other hand, acompressive sensing-inspired reconstruction algorithm, known as adaptivedictionary based statistical iterative reconstruction (ADSIR), has beenreported for x-ray computed tomography. In this paper, we evaluate the EST,ADSIR and an ordered-subset simultaneous algebraic reconstruction technique(OS-SART), and compare the ES and equally angled (EA) data acquisition modes.Our results show that OS-SART is comparable to EST, and the ADSIR outperformsEST and OS-SART. Furthermore, the equally sloped projection data acquisitionmode has no advantage over the conventional equally angled mode in the context.