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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

(DOI: 10.1016/j.patcog.2020.107705)

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,

(DOI: 10.1002/gamm.202100004)

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

(DOI: 10.1148/ryai.2021210011)

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

(DOI: 10.1016/j.media.2020.101933)

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

(DOI: 10.1016/j.media.2020.101930)

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)

199

(DOI: 10.1038/s42256-021-00307-0)

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

(DOI: 10.1038/s41598-021-82760-w)

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

(DOI: 10.1109/TIP.2021.3062726)

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

(DOI: 10.1016/j.media.2020.101941)

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

(DOI: 10.1088/1361-6420/abc531)

Data driven regularization by projection

A Aspri, Y Korolev, O Scherzer

– Inverse Problems

(2020)

36,

125009

(DOI: 10.1088/1361-6420/abb61b)

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

(DOI: 10.1109/tmi.2020.3017353)

Higher-Order Total Directional Variation: Imaging Applications

S Parisottoy, J Lellmannz, S Masnoux, CB Schönlieb

– SIAM J. Imaging Sci.

(2020)

13,

2063

(DOI: 10.1137/19m1239209)

Structural analysis of an $L$-infinity variational problem and relations to distance functions

L Bungert, Y Korolev, M Burger

– Pure and Applied Analysis

(2020)

703

(DOI: 10.2140/paa.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

(DOI: 10.1088/1361-6420/abc961)

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

(DOI: 10.1088/1361-6420/abb8e9)

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

(DOI: 10.1007/978-3-030-60365-6_18)

Accelerating variance-reduced stochastic gradient methods

D Driggs, MJ Ehrhardt, CB Schönlieb

– Mathematical Programming

(2020)

(DOI: 10.1007/s10107-020-01566-2)

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,

(DOI: 10.1109/MLSP49062.2020.9231874)

Multilevel Sequential Importance Sampling for Rare Event Estimation

F Wagner, J Latz, I Papaioannou, E Ullmann

– SIAM Journal on Scientific Computing

(2020)

42,

a2062

(DOI: 10.1137/19m1289601)

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