The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …

This review highlights recent efforts on applying electron microscopy (EM) to soft (including
biological) nanomaterials. We will show how developments of both the hardware and …

In the last few years, electron microscopy has experienced a new methodological paradigm
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …

Deep neural networks have demonstrated promising potential for the field of medical image
reconstruction, successfully generating high quality images for CT, PET and MRI. In this …

Neutron and x-ray scattering represent two classes of state-of-the-art materials
characterization techniques that measure materials structural and dynamical properties with …

Medical images are a rich source of invaluable necessary information used by clinicians.
Recent technologies have introduced many advancements for exploiting the most of this …

The segmentation of tomographic images of the battery electrode is a crucial processing
step, which will have an additional impact on the results of material characterization and …

For proton exchange membrane fuel cells to be cost‐competitive in light‐and heavy‐duty
vehicle applications, their Pt content in the catalyst layers needs to be lowered. However …

In many applications of tomography, the acquired data are limited in one or more ways due
to unavoidable experimental constraints. In such cases, popular direct reconstruction …

Synchrotron-based x-ray tomography is a noninvasive imaging technique that allows for
reconstructing the internal structure of materials at high spatial resolutions from tens of …