This review provides an introduction to—and overview of—the current state of the art in
neural‐network based regularization methods for inverse problems in imaging. It aims to …

Accurate segmentation of the jaw (ie, mandible and maxilla) and the teeth in cone beam
computed tomography (CBCT) scans is essential for orthodontic diagnosis and treatment …

In this paper we describe an investigation into the application of deep learning methods for
low-dose and sparse angle computed tomography using small training datasets. To motivate …

In this paper, we present Neural Adaptive Tomography (NeAT), the first adaptive,
hierarchical neural rendering pipeline for tomography. Through a combination of neural …

X‐ray tomography is a versatile tool in materials research and engineering since it allows for
a non‐destructive and three‐dimensional map** of the constituents of a heterogeneous …

Recovering a high-quality image from noisy indirect measurements is an important problem
with many applications. For such inverse problems, supervised deep convolutional neural …

X-ray computed tomography (CT) is frequently used for non-destructive testing with many
applications in a wide range of scientific research areas. The difference in imaging speeds …

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s.
Online analysis methods are needed to enable the collection of only interesting subsets of …

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 …

Quality control in metal additive manufacturing prioritizes the development of advanced
inspection schemes to characterize the defect evolution during processing and post …