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ORCIDJohannes Leuschner
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2020 – today
- 2024
[j7]Tom Lütjen
, Fabian Schönfeld, Alice Oberacker, Johannes Leuschner, Maximilian Schmidt, Anne Wald, Tobias Kluth:
Learning-Based Approaches for Reconstructions With Inexact Operators in nanoCT Applications. IEEE Trans. Computational Imaging 10: 522-534 (2024)- [j6]Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, Zeljko Kereta:
Image Reconstruction via Deep Image Prior Subspaces. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [b1]Johannes Leuschner:
Deep learning for computed tomography reconstruction - learned methods, deep image prior and uncertainty estimation. Bremen University, Germany, 2023 - [j5]Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin:
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior. Trans. Mach. Learn. Res. 2023 (2023) - [c1]Marco Nittscher, Michael Falk Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass:
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. MIDL 2023: 617-642 - [i9]Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Zeljko Kereta, Bangti Jin:
Fast and Painless Image Reconstruction in Deep Image Prior Subspaces. CoRR abs/2302.10279 (2023) - [i8]Marco Nittscher, Michael Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass:
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. CoRR abs/2303.15748 (2023) - [i7]Tom Lütjen, Fabian Schönfeld, Alice Oberacker, Johannes Leuschner, Maximilian Schmidt, Anne Wald, Tobias Kluth:
Learning-based approaches for reconstructions with inexact operators in nanoCT applications. CoRR abs/2307.10474 (2023) - 2022
- [j4]Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maass, Bangti Jin:
An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction. IEEE Trans. Computational Imaging 8: 1210-1222 (2022) - [i6]Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin:
A Probabilistic Deep Image Prior for Computational Tomography. CoRR abs/2203.00479 (2022) - [i5]Riccardo Barbano, Johannes Leuschner, Javier Antorán, Bangti Jin, José Miguel Hernández-Lobato:
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior. CoRR abs/2207.05714 (2022) - 2021
- [j3]Johannes Leuschner, Maximilian Schmidt, Poulami Somanya Ganguly, Vladyslav Andriiashen, Sophia Bethany Coban, Alexander Denker, Dominik F. Bauer, Amir Hadjifaradji, Kees Joost Batenburg, Peter Maass, Maureen van Eijnatten:
Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications. J. Imaging 7(3): 44 (2021) - [j2]Alexander Denker, Maximilian Schmidt, Johannes Leuschner, Peter Maass:
Conditional Invertible Neural Networks for Medical Imaging. J. Imaging 7(11): 243 (2021) - [i4]Sören Schulze, Johannes Leuschner, Emily J. King:
Training a Deep Neural Network via Policy Gradients for Blind Source Separation in Polyphonic Music Recordings. CoRR abs/2107.04235 (2021) - [i3]Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maaß, Bangti Jin:
Is Deep Image Prior in Need of a Good Education? CoRR abs/2111.11926 (2021) - 2020
- [i2]Daniel Otero Baguer, Johannes Leuschner, Maximilian Schmidt:
Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods. CoRR abs/2003.04989 (2020)
2010 – 2019
- 2019
- [j1]Johannes Leuschner, Maximilian Schmidt, Pascal Fernsel, Delf Lachmund, Tobias Boskamp, Peter Maass:
Supervised non-negative matrix factorization methods for MALDI imaging applications. Bioinform. 35(11): 1940-1947 (2019) - [i1]Johannes Leuschner, Maximilian Schmidt, Daniel Otero Baguer, Peter Maaß:
The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods. CoRR abs/1910.01113 (2019)
Coauthor Index
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