| 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 | 294 | 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 | 153 | 2009 |
| Noise2Inverse: Self-supervised deep convolutional denoising for tomography AA Hendriksen, DM Pelt, KJ Batenburg IEEE Transactions on Computational Imaging 6, 1320-1335, 2020 | 139 | 2020 |
| 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 | 131 | 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 | 130 | 2018 |
| Fast tomographic reconstruction from limited data using artificial neural networks DM Pelt, KJ Batenburg Image Processing, IEEE Transactions on 22 (12), 5238-5251, 2013 | 123 | 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 | 91 | 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 | 76 | 2019 |
| Improving filtered backprojection reconstruction by data-dependent filtering DM Pelt, KJ Batenburg Image Processing, IEEE Transactions on 23 (11), 4750-4762, 2014 | 60 | 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 | 48 | 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 | 42 | 2020 |
| 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 | 36 | 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 | 34 | 2021 |
| 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 | 34 | 2015 |
| Ring artifact reduction in synchrotron x-ray tomography through helical acquisition DM Pelt, DY Parkinson Measurement Science and Technology 29 (3), 034002, 2018 | 25 | 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 | 25 | 2017 |
| Accurately approximating algebraic tomographic reconstruction by filtered backprojection DM Pelt, KJ Batenburg Proceedings of The 13th International Meeting on Fully Three-Dimensional …, 2015 | 25 | 2015 |
| Tomosipo: fast, flexible, and convenient 3D tomography for complex scanning geometries in Python AA Hendriksen, D Schut, WJ Palenstijn, N Viganó, J Kim, DM Pelt, ... Optics Express 29 (24), 40494-40513, 2021 | 21 | 2021 |
| 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 | 20 | 2017 |
| An analysis of the impact of annotation errors on the accuracy of deep learning for cell segmentation Ş Vădineanu, DM Pelt, O Dzyubachyk, KJ Batenburg International Conference on Medical Imaging with Deep Learning, 1251-1267, 2022 | 18 | 2022 |
