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  • Currently displaying 141 - 160 of 269 publications
Automated Quantification of Photoreceptor alteration in macular disease using Optical Coherence Tomography and Deep Learning
JI Orlando, BS Gerendas, S Riedl, C Grechenig, A Breger, M Ehler, SM Waldstein, H Bogunović, U Schmidt-Erfurth
– Scientific reports
(2020)
10,
5619
(doi: 10.1038/s41598-020-62329-9)
Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination
D Kimanius, G Zickert, T Nakane, J Adler, S Lunz, C-B Schönlieb, O Öktem, SHW Scheres
(2020)
2020.03.25.007914
(doi: 10.1101/2020.03.25.007914)
Higher-order total directional variation: Analysis
S Parisotto, S Masnou, CB Schönlieb
– SIAM Journal on Imaging Sciences
(2020)
13,
474
(doi: 10.1137/19m1239210)
Analysis of Artifacts in Shell-Based Image Inpainting: Why They Occur and How to Eliminate Them
LR Hocking, T Holding, C-B Schoenlieb
– Foundations of Computational Mathematics
(2020)
20,
1549
(doi: 10.1007/s10208-020-09450-3)
A variational model dedicated to joint segmentation, registration, and atlas generation for shape analysis
N Debroux, J Aston, F Bonardi, A Forbes, C Le Guyader, M Romanchikova, CB Schonlieb
– SIAM Journal on Imaging Sciences
(2020)
13,
351
(doi: 10.1137/19m1271907)
A hybrid analytical-numerical algorithm for determining the neuronal current via electroencephalography
P Hashemzadeh, AS Fokas, CB Schönlieb
– Journal of The Royal Society Interface
(2020)
17,
20190831
(doi: 10.1098/rsif.2019.0831)
Bregman Itoh-Abe Methods for Sparse Optimisation
M Benning, ES Riis, CB Schönlieb
– Journal of Mathematical Imaging and Vision
(2020)
62,
842
(doi: 10.1007/s10851-020-00944-x)
Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC)
J Williams, C Schoenlieb, T Swinfield, J Lee, X Cai, L Qie, D Coomes
– IEEE Transactions on Geoscience and Remote Sensing
(2020)
58,
754
(doi: 10.1109/TGRS.2019.2940146)
3D Segmentation of Trees through a Flexible Multiclass Graph Cut Algorithm
J Williams, CB Schonlieb, T Swinfield, J Lee, X Cai, L Qie, DA Coomes
(2020)
(doi: 10.1109/tgrs.2019.2940146)
A multi‐contrast MRI approach to thalamus segmentation
V Corona, J Lellmann, P Nestor, C-B Schönlieb, J Acosta-Cabronero
– Human Brain Mapping
(2020)
abs/1807.10757,
2104
(doi: 10.1002/hbm.24933)
Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification
P Sellars, AI Aviles-Rivero, CB Schonlieb
– IEEE Transactions on Geoscience and Remote Sensing
(2020)
58,
4180
(doi: 10.1109/tgrs.2019.2961599)
Classification of Human Gait Acceleration Data Using Convolutional Neural Networks
D Kreuter, H Takahashi, Y Omae, T Akiduki, Z Zhang
– International Journal of Innovative Computing, Information and Control
(2020)
16,
609
(doi: 10.24507/ijicic.16.02.609)
Deeply learned spectral total variation decomposition
TG Grossmann, Y Korolev, G Gilboa, CB Schönlieb
– Advances in Neural Information Processing Systems
(2020)
2020-December,
(link to publication)
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review.
M Roberts, D Driggs, M Thorpe, JD Gilbey, M Yeung, S Ursprung, AI Avilés-Rivero, C Etmann, C McCague, L Beer, JR Weir-McCall, Z Teng, JHF Rudd, E Sala, C-B Schönlieb
– CoRR
(2020)
abs/2008.06388,
Improving a Stochastic Algorithm for Regularized PET Image Reconstruction
C Delplancke, M Gurnell, J Latz, PJ Markiewicz, CB Schönlieb, MJ Ehrhardt
– 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
(2020)
00,
1
(doi: 10.1109/NSS/MIC42677.2020.9508013)
Tuning-free plug-and-play proximal algorithm for inverse imaging problems
K Wei, A Aviles-Rivero, J Liang, Y Fu, CB Schönlieb, H Huang
– 37th International Conference on Machine Learning, ICML 2020
(2020)
PartF168147-14,
10089
(link to publication)
Linkage between piecewise constant mumford-shah model and rudin-osher-fatemi model and its virtue in image segmentation
X Cai, R Chan, CB Schönlieb, G Steidl, T Zeng
– SIAM Journal on Scientific Computing
(2019)
41,
B1310
(doi: 10.1137/18M1202980)
Deep learning as optimal control problems: Models and numerical methods
M Benning, E Celledoni, MJ Ehrhardt, B Owren, CB Schönlieb
– Journal of Computational Dynamics
(2019)
6,
171
(doi: 10.3934/jcd.2019009)
Faster PET reconstruction with non-smooth priors by randomization and preconditioning
MJ Ehrhardt, P Markiewicz, C-B Schönlieb
– Physics in Medicine & Biology
(2019)
64,
225019
(doi: 10.1088/1361-6560/ab3d07)
On Orthogonal Projections for Dimension Reduction and Applications in Augmented Target Loss Functions for Learning Problems
A Breger, JI Orlando, P Harar, M Dörfler, S Klimscha, C Grechenig, BS Gerendas, U Schmidt-Erfurth, M Ehler
– Journal of Mathematical Imaging and Vision
(2019)
62,
376
(doi: 10.1007/s10851-019-00902-2)

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