Task-Adaptive Angle Selection for Computed Tomography-Based Defect Detection

Autor: Tianyuan Wang, Virginia Florian, Richard Schielein, Christian Kretzer, Stefan Kasperl, Felix Lucka, Tristan van Leeuwen

Publikováno v: Journal of Imaging, Vol 10, Iss 9, p 208 (2024)

Sparse-angle X-ray Computed Tomography (CT) plays a vital role in industrial quality control but leads to an inherent trade-off between scan time and reconstruction quality. Adaptive angle selection strategies try to improve upon this based on the id

Externí odkaz: https://doaj.org/article/622094910521431e851d7b6c76a0b4e2

Unsupervised deep learning for defect detection on CT parts using simulated data

Autor: Virginia Florian, Christian Kretzer, Stefan Kasperl, Richard Schielein, Benjamin Montavon, Robert H. Schmitt

Publikováno v: Research and Review Journal of Nondestructive Testing, Vol 1, Iss 1 (2023)

Computed tomography (CT) is a prominent technology for nondestructive quality control and is already used in industry for defect detection. However, as quality control is shifting towards a full in-line inspection, automatic CT analysis is required t

Externí odkaz: https://doaj.org/article/63e3f83cfb2d4128876ba46079ad0b69

Comparing image quality in phase contrast sub$\mu$ X-ray tomography—A round-robin study

Autor: P. Lhuissier, Richard Schielein, Simon Zabler, Randolf Hanke, Maximilian Ullherr, Berit Zeller-Plumhoff, Christian Fella, O. Focke, W. DeBoever

Publikováno v: Nucl.Instrum.Meth.A
Nucl.Instrum.Meth.A, 2020, 951, pp.162992. ⟨10.1016/j.nima.2019.162992⟩
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Elsevier, 2020, 951, pp.162992. ⟨10.1016/j.nima.2019.162992⟩

International audience; How to evaluate and compare image quality from different sub-micrometer (sub μ ) CT scans? A simple test phantom made of polymer microbeads is used for recording projection images as well as 13 CT scans in a number of commerc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dde09b4bf1dffead38cac6fa69a2a649
https://hal.archives-ouvertes.fr/hal-02221549

Transfer Learning from Synthetic Data Applied to Soil–Root Segmentation in X-Ray Tomography Images

Autor: Richard Schielein, Stefan Gerth, David Rousseau, Carole Frindel, Clément Douarre

Publikováno v: Journal of Imaging
Journal of Imaging, MDPI, 2018, 4 (5), pp.65. ⟨10.3390/jimaging4050065⟩
www.mdpi.com/journal/jimaging
Journal of Imaging; Volume 4; Issue 5; Pages: 65
Journal of Imaging 5 (4), 65. (2018)

International audience; One of the most challenging computer vision problems in the plant sciences is the segmentation of roots and soil in X-ray tomography. So far, this has been addressed using classical image analysis methods. In this paper, we ad

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e07fa00c82808be91acfb315a1b000ac
https://hal.inrae.fr/hal-02624298/file/2018_Douarre_J.Imaging_1.pdf

Monte Carlo X-ray scattering studies in the MeV regime

Autor: Markus Kiunke Richard Schielein Killian Dremel Simon Zabler Frank Sukowski Stefan Kasperl

A study is shown which is performed to enhance an existing deterministic X ray simulation method for nondestructive testing applications by including the effect of pair production and annihilation. Therefore a Monte Carlo simulation tool was used to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=snsf_p3_pubs::684ae4436e2da77cab4cabbb0ddb789e
http://www.ndt.net/events/ECNDT2014/app/content/Paper/361_Kiunke_Rev1.pdf