Zobrazeno 1 - 10
of 126
pro vyhledávání: '"Kees Joost Batenburg"'
Publikováno v:
Journal of Imaging, Vol 10, Iss 7, p 172 (2024)
Deep-learning algorithms for cell segmentation typically require large data sets with high-quality annotations to be trained with. However, the annotation cost for obtaining such sets may prove to be prohibitively expensive. Our work aims to reduce t
Externí odkaz:
https://doaj.org/article/54909f79d8f54aa1987cc979550a3b43
Publikováno v:
Journal of Synchrotron Radiation, Vol 29, Iss 1, Pp 254-265 (2022)
Tomographic algorithms are often compared by evaluating them on certain benchmark datasets. For fair comparison, these datasets should ideally (i) be challenging to reconstruct, (ii) be representative of typical tomographic experiments, (iii) be flex
Externí odkaz:
https://doaj.org/article/04ec794b2ba042cba531004ab3f2e4c9
Publikováno v:
Journal of Imaging, Vol 7, Iss 7, p 104 (2021)
X-ray imaging is a widely used technique for non-destructive inspection of agricultural food products. One application of X-ray imaging is the autonomous, in-line detection of foreign objects in food samples. Examples of such inclusions are bone frag
Externí odkaz:
https://doaj.org/article/8055f03819404d1da705f113a8b319bf
Autor:
Johannes Leuschner, Maximilian Schmidt, Poulami Somanya Ganguly, Vladyslav Andriiashen, Sophia Bethany Coban, Alexander Denker, Dominik Bauer, Amir Hadjifaradji, Kees Joost Batenburg, Peter Maass, Maureen van Eijnatten
Publikováno v:
Journal of Imaging, Vol 7, Iss 3, p 44 (2021)
The reconstruction of computed tomography (CT) images is an active area of research. Following the rise of deep learning methods, many data-driven models have been proposed in recent years. In this work, we present the results of a data challenge tha
Externí odkaz:
https://doaj.org/article/a9c9ce94377745e8adb2466faaf9be04
Autor:
Mathé T. Zeegers, Daniël M. Pelt, Tristan van Leeuwen, Robert van Liere, Kees Joost Batenburg
Publikováno v:
Journal of Imaging, Vol 6, Iss 12, p 132 (2020)
An important challenge in hyperspectral imaging tasks is to cope with the large number of spectral bins. Common spectral data reduction methods do not take prior knowledge about the task into account. Consequently, sparsely occurring features that ma
Externí odkaz:
https://doaj.org/article/1018fe423f94464dafb9bc0059fba8f1
Publikováno v:
Journal of Imaging, Vol 6, Iss 12, p 135 (2020)
Circular cone-beam (CCB) Computed Tomography (CT) has become an integral part of industrial quality control, materials science and medical imaging. The need to acquire and process each scan in a short time naturally leads to trade-offs between speed
Externí odkaz:
https://doaj.org/article/ea4fd5d8a1f04b1bbec810517b5b0736
Autor:
Nicola Viganò, Felix Lucka, Ombeline de La Rochefoucauld, Sophia Bethany Coban, Robert van Liere, Marta Fajardo, Philippe Zeitoun, Kees Joost Batenburg
Publikováno v:
Journal of Imaging, Vol 6, Iss 12, p 138 (2020)
X-ray plenoptic cameras acquire multi-view X-ray transmission images in a single exposure (light-field). Their development is challenging: designs have appeared only recently, and they are still affected by important limitations. Concurrently, the la
Externí odkaz:
https://doaj.org/article/a0a465c8d3374cf0a7d65b07ac5358e6
Autor:
Sophia Bethany Coban, Felix Lucka, Willem Jan Palenstijn, Denis Van Loo, Kees Joost Batenburg
Publikováno v:
Journal of Imaging, Vol 6, Iss 4, p 18 (2020)
In tomographic imaging, the traditional process consists of an expert and an operator collecting data, the expert working on the reconstructed slices and drawing conclusions. The quality of reconstructions depends heavily on the quality of the collec
Externí odkaz:
https://doaj.org/article/ad2f71d632994721a00f86f54ea924e2
Autor:
Allard A. Hendriksen, Daniël M. Pelt, Willem Jan Palenstijn, Sophia B. Coban, Kees Joost Batenburg
Publikováno v:
Applied Sciences, Vol 9, Iss 12, p 2445 (2019)
In tomography, the resolution of the reconstructed 3D volume is inherently limited by the pixel resolution of the detector and optical phenomena. Machine learning has demonstrated powerful capabilities for super-resolution in several imaging applicat
Externí odkaz:
https://doaj.org/article/bbab0ae8f7194192b74639df1360f077
Publikováno v:
Journal of Imaging, Vol 4, Iss 11, p 128 (2018)
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 algorithms tend to produce inaccurate images, and more accurate iterative
Externí odkaz:
https://doaj.org/article/9c73422a48404e7e9b50001536d0a72e