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  • Currently displaying 1 - 20 of 189 publications
Dynamic spectral residual superpixels
J Zhang, AI Aviles-Rivero, D Heydecker, X Zhuang, R Chan, CB Schönlieb
– Pattern Recognition
(2021)
112,
107705
Classification and image processing with a semi‐discrete scheme for fidelity forced Allen–Cahn on graphs
J Budd, Y van Gennip, J Latz
– GAMM Mitteilungen
(2021)
44,
Machine Learning for COVID-19 Diagnosis and Prognostication: Lessons for Amplifying the Signal While Reducing the Noise
D Driggs, I Selby, M Roberts, E Gkrania-Klotsas, JHF Rudd, G Yang, J Babar, E Sala, C-B Schönlieb
– Radiology Artificial Intelligence
(2021)
e210011
Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction.
AI Aviles-Rivero, N Debroux, G Williams, MJ Graves, C-B Schönlieb
– Medical Image Analysis
(2021)
abs/1810.10828,
101933
Rethinking medical image reconstruction via shape prior, going deeper and faster: Deep joint indirect registration and reconstruction
J Liu, AI Aviles-Rivero, H Ji, C-B Schönlieb
– Med Image Anal
(2021)
68,
101930
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, AI Aviles-Rivero, C Etmann, C McCague, L Beer, JR Weir-McCall, Z Teng, E Gkrania-Klotsas, A Ruggiero, A Korhonen, E Jefferson, E Ako, G Langs, G Gozaliasl, G Yang, H Prosch, J Preller, J Stanczuk, J Tang, J Hofmanninger, J Babar, LE Sánchez, M Thillai, PM Gonzalez, P Teare, X Zhu, M Patel, C Cafolla, H Azadbakht, J Jacob, J Lowe, K Zhang, K Bradley, M Wassin, M Holzer, K Ji, MD Ortet, T Ai, N Walton, P Lio, S Stranks, T Shadbahr, W Lin, Y Zha, Z Niu, JHF Rudd, E Sala, CB Schönlieb
– Nature Machine Intelligence
(2021)
3,
199
Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events
EPV Le, L Rundo, JM Tarkin, NR Evans, MM Chowdhury, PA Coughlin, H Pavey, C Wall, F Zaccagna, FA Gallagher, Y Huang, R Sriranjan, A Le, JR Weir-McCall, M Roberts, FJ Gilbert, EA Warburton, C-B Schönlieb, E Sala, JHF Rudd
– Scientific reports
(2021)
11,
3499
Multi-Task Deep Learning for Image Segmentation Using Recursive Approximation Tasks.
R Ke, A Bugeau, N Papadakis, M Kirkland, P Schuetz, C-B Schonlieb
– IEEE Trans Image Process
(2021)
30,
3555
Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution
V Corona, AI Aviles-Rivero, N Debroux, CL Guyader, C-B Schönlieb
– Medical Image Analysis
(2020)
68,
101941
Variational regularisation for inverse problems with imperfect forward operators and general noise models.
L Bungert, M Burger, Y Korolev, CB Schönlieb
– CoRR
(2020)
36,
125014
Data driven regularization by projection
A Aspri, Y Korolev, O Scherzer
– Inverse Problems
(2020)
36,
125009
Learning the Sampling Pattern for MRI.
F Sherry, M Benning, JC De Los Reyes, MJ Graves, G Maierhofer, G Williams, C-B Schonlieb, MJ Ehrhardt
– IEEE transactions on medical imaging
(2020)
39,
4310
Higher-Order Total Directional Variation: Imaging Applications
S Parisottoy, J Lellmannz, S Masnoux, CB Schönlieb
– SIAM J. Imaging Sci.
(2020)
13,
2063
Structural analysis of an $L$-infinity variational problem and relations to distance functions
L Bungert, Y Korolev, M Burger
– Pure and Applied Analysis
(2020)
2,
703
Scanning electron diffraction tomography of strain
R Tovey, DN Johnstone, SM Collins, WRB Lionheart, PA Midgley, M Benning, C-B Schönlieb
– Inverse Problems
(2020)
37,
015003
Preface for the special issue ‘Variational methods and effective algorithms for imaging and vision’
CB Schonlieb, M Hintermuller, S Arridge
– Inverse Problems
(2020)
36,
110401
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-supervised Framework for Medical Image Classification
M de Vriendt, P Sellars, AI Aviles-Rivero
– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
(2020)
12443 LNCS,
187
Accelerating variance-reduced stochastic gradient methods
D Driggs, MJ Ehrhardt, CB Schönlieb
– Mathematical Programming
(2020)
1
iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems
C Etmann, R Ke, CB Schonlieb
– IEEE International Workshop on Machine Learning for Signal Processing, MLSP
(2020)
2020-September,
1
Multilevel Sequential Importance Sampling for Rare Event Estimation
F Wagner, J Latz, I Papaioannou, E Ullmann
– SIAM Journal on Scientific Computing
(2020)
42,
a2062