Daniël M. Pelt
Daniël M. Pelt
Assistant Professor at Leiden University
Geverifieerd e-mailadres voor liacs.leidenuniv.nl - Homepage
Geciteerd door
Geciteerd door
A mixed-scale dense convolutional neural network for image analysis
DM Pelt, JA Sethian
Proceedings of the National Academy of Sciences 115 (2), 254-259, 2018
Efficient method for predicting crystal structures at finite temperature: Variable box shape simulations
L Filion, M Marechal, B van Oorschot, D Pelt, F Smallenburg, M Dijkstra
Physical review letters 103 (18), 188302, 2009
Integration of TomoPy and the ASTRA toolbox for advanced processing and reconstruction of tomographic synchrotron data
DM Pelt, D Gürsoy, WJ Palenstijn, J Sijbers, F De Carlo, KJ Batenburg
Journal of Synchrotron Radiation 23 (3), 842-849, 2016
Improving Tomographic Reconstruction from Limited Data Using Mixed-Scale Dense Convolutional Neural Networks
D Pelt, K Batenburg, J Sethian
Journal of Imaging 4 (11), 128, 2018
Noise2Inverse: Self-supervised deep convolutional denoising for tomography
AA Hendriksen, DM Pelt, KJ Batenburg
IEEE Transactions on Computational Imaging 6, 1320-1335, 2020
Fast tomographic reconstruction from limited data using artificial neural networks
DM Pelt, KJ Batenburg
Image Processing, IEEE Transactions on 22 (12), 5238-5251, 2013
TomoBank: a tomographic data repository for computational x-ray science
F De Carlo, D Gürsoy, DJ Ching, KJ Batenburg, W Ludwig, L Mancini, ...
Measurement Science and Technology 29 (3), 034004, 2018
Segmentation of dental cone‐beam CT scans affected by metal artifacts using a mixed‐scale dense convolutional neural network
J Minnema, M van Eijnatten, AA Hendriksen, N Liberton, DM Pelt, ...
Medical physics 46 (11), 5027-5035, 2019
Improving filtered backprojection reconstruction by data-dependent filtering
DM Pelt, KJ Batenburg
Image Processing, IEEE Transactions on 23 (11), 4750-4762, 2014
A medium-grain method for fast 2D bipartitioning of sparse matrices
DM Pelt, RH Bisseling
International Parallel and Distributed Processing Symposium, 2014. IPDPS …, 2014
Pushing the temporal resolution in absorption and Zernike phase contrast nanotomography: enabling fast in situ experiments
S Flenner, M Storm, A Kubec, E Longo, F Döring, DM Pelt, C David, ...
Journal of synchrotron radiation 27 (5), 1339-1346, 2020
Electron tomography based on highly limited data using a neural network reconstruction technique
E Bladt, DM Pelt, S Bals, KJ Batenburg
Ultramicroscopy 158, 81-88, 2015
Real-time reconstruction and visualisation towards dynamic feedback control during time-resolved tomography experiments at TOMCAT
JW Buurlage, F Marone, DM Pelt, WJ Palenstijn, M Stampanoni, ...
Scientific reports 9 (1), 18379, 2019
Deep denoising for multi-dimensional synchrotron X-ray tomography without high-quality reference data
AA Hendriksen, M Bührer, L Leone, M Merlini, N Vigano, DM Pelt, ...
Scientific reports 11 (1), 11895, 2021
Accurately approximating algebraic tomographic reconstruction by filtered backprojection
DM Pelt, KJ Batenburg
Proceedings of The 13th International Meeting on Fully Three-Dimensional …, 2015
Ring artifact reduction in synchrotron x-ray tomography through helical acquisition
DM Pelt, DY Parkinson
Measurement Science and Technology 29 (3), 034002, 2018
Insight into 3D micro-CT data: exploring segmentation algorithms through performance metrics
T Perciano, D Ushizima, H Krishnan, D Parkinson, N Larson, DM Pelt, ...
Journal of synchrotron radiation 24 (5), 1065-1077, 2017
Machine learning for micro-tomography
DY Parkinson, DM Pelt, T Perciano, D Ushizima, H Krishnan, HS Barnard, ...
Developments in X-Ray Tomography XI 10391, 85-92, 2017
Improved tomographic reconstruction of large-scale real-world data by filter optimization
DM Pelt, V De Andrade
Advanced Structural and Chemical Imaging 2 (1), 17, 2017
On-the-Fly Machine Learning for Improving Image Resolution in Tomography
AA Hendriksen, DM Pelt, WJ Palenstijn, SB Coban, KJ Batenburg
Applied Sciences 9 (12), 2445, 2019
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