Deep-XFCT: Deep Learning 3D-Mineral Liberation Analysis with Micro-X-ray Fluorescence and Computed Tomography

Deep Learning Computed Tomography

In this paper, we demonstrate that image reconstruction can be expressed in terms of neural networks. We show that filtered backprojection can be mapped identically onto a deep neural network architecture. As for the case of iterative reconstruction, the straight forward realization as matrix multiplication is not feasible. Thus, we propose to compute the back-projection layer efficiently as fi...

X-ray micro-computed tomography

Micro-computed tomography (μCT) has been successfully used to study the cardiovascular system of mouse embryos in situ. With the use of barium as a suitablecontrast agent, blood vessels have beenimaged and analysed quantitatively such asblood volume and vessel sizes on embryosof ages 14.5 to 16.5 days old. The advantageof using this imaging modality is that it hasprovide...

Subsurface Particle Analysis using X-ray Computed Tomography and Confocal X- ray Fluorescence

Investigating porosity of sintering porous copper structure with 3D micro-focus X-ray computed tomography (μCT)

Purpose: The paper presents studies on the structure intended to form a heat exchange element made of sintered porous Cu. Design/methodology/approach: Analyses of Cu foam exhibiting a cellular structure have been carried out using X-ray tomography. Findings: Samples of copper foam have been imaged at high resolution using a large-field, 3D micro-focus X-ray computed tomography (μCT) system, thr...

X-ray computed tomography.

X-ray computed tomography (CT), introduced into clinical practice in 1972, was the first of the modern slice-imaging modalities. To reconstruct images mathematically from measured data and to display and to archive them in digital form was a novelty then and is commonplace today. CT has shown a steady upward trend with respect to technology, performance and clinical use independent of predictio...