Related papers: Quantifying the effect of X-ray scattering for dat…
Surface inspection systems are an important application domain for computer vision, as they are used for defect detection and classification in the manufacturing industry. Existing systems use hand-crafted features which require extensive…
Neutron and x-ray scattering experiments traditionally rely upon histogrammed data sets, which are analysed using least-squares curve fitting of multiple probability distribution components to quantify separately the various scientific…
A key diagnostic in warm-dense matter (WDM) experiments is X-ray Thomson scattering (XRTS), but its interpretation is often limited by complex instrument effects and the high computationally expensive combinations of microscopic models with…
Scattering networks are a class of designed Convolutional Neural Networks (CNNs) with fixed weights. We argue they can serve as generic representations for modelling images. In particular, by working in scattering space, we achieve…
With increasing patient and staff X-ray radiation awareness, many efforts have been made to develop accurate patient dose estimation methods. To date, Monte Carlo (MC) simulations are considered golden standard to simulate the interaction…
Algorithmic X-ray scatter compensation is a desirable technique in flat-panel X-ray imaging and cone-beam computed tomography. State-of-the-art U-net based image translation approaches yielded promising results. As there are no physics…
Small angle scattering by dust grains causes a significant contribution to the total interstellar extinction for any X-ray instrument with sub-arcminute resolution (Chandra, Swift, XMM-Newton). However, the dust scattering component is not…
New production techniques have emerged that have made it possible to produce metal parts with more complex shapes, making the quality control process more difficult. This implies that the visual and superficial analysis has become even more…
Our interest has been to study the effect that scattered radiation has on contrast, signal-to-noise ratio and thickness reconstruction in digital mammographies. Using the GEANT code we have performed Monte-Carlo simulations of 25 kVp Mo/Mo…
In industry, defect detection is crucial for quality control. Non-destructive testing (NDT) methods are preferred as they do not influence the functionality of the object while inspecting. Automated data evaluation for automated defect…
In several image acquisition and processing steps of X-ray radiography, knowledge of the existence of metal implants and their exact position is highly beneficial (e.g. dose regulation, image contrast adjustment). Another application which…
In computed tomography (CT) reconstruction, scattering causes server quality degradation of the reconstructed CT images by introducing streaks and cupping artifacts which reduce the detectability of low contrast objects. Monte Carlo (MC)…
When an X-ray area detector based on a single crystalline material, for instance, a state of the art hybrid pixel detector, is illuminated from a point source by monochromatic radiation, a pattern of lines appears which overlays the…
Defects are unavoidable in casting production owing to the complexity of the casting process. While conventional human-visual inspection of casting products is slow and unproductive in mass productions, an automatic and reliable defect…
Scatter signals can degrade the contrast and resolution of computed tomography (CT) images and induce artifacts. How to effectively correct scatter signals in CT has always been a focal point of research for researchers. This work presents…
This paper presents a new method to model X-ray scattering on random rough surfaces. It combines the approaches we presented in two previous papers -- \zs\cite{zhao03} \& \pz\cite{zhao15}. An actual rough surface is (incompletely) described…
Automated detection of contraband items in X-ray images can significantly increase public safety, by enhancing the productivity and alleviating the mental load of security officers in airports, subways, customs/post offices, etc. The large…
In industrial settings, surface defects on steel can significantly compromise its service life and elevate potential safety risks. Traditional defect detection methods predominantly rely on manual inspection, which suffers from low…
In this work, we compare one-step and two-step approaches for X-ray computed tomography (CT) scatter correction and density reconstruction. X-ray CT is an important imaging technique in medical and industrial applications. In many cases,…
Defect detection is one of the most important yet challenging tasks in the quality control stage in the manufacturing sector. In this work, we introduce a Tensor Convolutional Neural Network (T-CNN) and examine its performance on a real…