Multi-resolution Data Fusion for Super-Resolution Electron Microscopy

TL;DR

This paper introduces a multi-resolution data fusion method for electron microscopy that combines low- and high-resolution data to achieve super-resolution imaging, significantly improving resolution, speed, and reducing dosage in material and biological sciences.

Contribution

The paper presents a novel multi-resolution data fusion approach that integrates low- and high-resolution EM data using a material-specific patch-library within a plug-and-play framework, enabling super-resolution imaging.

Findings

Achieved super-resolution factors of 4x, 8x, and 16x.

Maintained high image quality while reducing electron dosage.

Demonstrated effectiveness on FEI electron microscope data.

Abstract

Perhaps surprisingly, the total electron microscopy (EM) data collected to date is less than a cubic millimeter. Consequently, there is an enormous demand in the materials and biological sciences to image at greater speed and lower dosage, while maintaining resolution. Traditional EM imaging based on homogeneous raster-order scanning severely limits the volume of high-resolution data that can be collected, and presents a fundamental limitation to understanding physical processes such as material deformation, crack propagation, and pyrolysis. We introduce a novel multi-resolution data fusion (MDF) method for super-resolution computational EM. Our method combines innovative data acquisition with novel algorithmic techniques to dramatically improve the resolution/volume/speed trade-off. The key to our approach is to collect the entire sample at low resolution, while simultaneously collecting a small fraction of data at high resolution. The high-resolution measurements are then used to create a material-specific patch-library that is used within the "plug-and-play" framework to dramatically improve super-resolution of the low-resolution data. We present results using FEI electron microscope data that demonstrate super-resolution factors of 4x, 8x, and 16x, while substantially maintaining high image quality and reducing dosage.