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Johannes Leuschner

Showing results (1-10 of 4) with videos related to

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Journal of Imaging|November 25, 2021
Conditional Invertible Neural Networks for Medical ImagingAlexander Denker, Maximilian Schmidt, Johannes Leuschner, et al.
Scientific Data|April 17, 2021
LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstructionJohannes Leuschner, Maximilian Schmidt, Daniel Otero Baguer, et al.
Bioinformatics (Oxford, England)|November 6, 2018
Supervised non-negative matrix factorization methods for MALDI imaging applicationsJohannes Leuschner, Maximilian Schmidt, Pascal Fernsel, et al.
Journal of Imaging|August 30, 2021
Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT ApplicationsJohannes Leuschner, Maximilian Schmidt, Poulami Somanya Ganguly, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

Sort By:
Pageof 1
Journal of Imaging|November 25, 2021
Conditional Invertible Neural Networks for Medical ImagingAlexander Denker, Maximilian Schmidt, Johannes Leuschner, et al.
Scientific Data|April 17, 2021
LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstructionJohannes Leuschner, Maximilian Schmidt, Daniel Otero Baguer, et al.
Bioinformatics (Oxford, England)|November 6, 2018
Supervised non-negative matrix factorization methods for MALDI imaging applicationsJohannes Leuschner, Maximilian Schmidt, Pascal Fernsel, et al.
Journal of Imaging|August 30, 2021
Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT ApplicationsJohannes Leuschner, Maximilian Schmidt, Poulami Somanya Ganguly, et al.
Pageof 1