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  • Currently displaying 1 - 20 of 273 publications
A study of why we need to reassess full reference image quality assessment with medical images
A Breger, A Biguri, M Sabaté Landman, I Selby, N Amberg, E Brunner, J Gröhl, S Hatamikia, C Kerner, L Ning, S Dittmer, M Roberts, C Schoenlieb
– Journal of Imaging Informatics in Medicine
(2025)
(doi: 10.1007/s10278-025-01462-1)
FCN+: Global receptive convolution makes FCN great again
X Ren, Z Deng, J Ye, J He, D Yang
– Neurocomputing
(2025)
631,
129655
(doi: 10.1016/j.neucom.2025.129655)
A-Eval: A benchmark for cross-dataset and cross-modality evaluation of abdominal multi-organ segmentation
Z Huang, Z Deng, J Ye, H Wang, Y Su, T Li, H Sun, J Cheng, J Chen, J He, Y Gu, S Zhang, L Gu, Y Qiao
– Med Image Anal
(2025)
101,
103499
(doi: 10.1016/j.media.2025.103499)
On the caveats of AI autophagy
X Xing, F Shi, J Huang, Y Wu, Y Nan, S Zhang, Y Fang, M Roberts, CB Schönlieb, J Del Ser, G Yang
– Nature Machine Intelligence
(2025)
7,
172
(doi: 10.1038/s42256-025-00984-1)
A Pipeline for Automated Quality Control of Chest Radiographs
IA Selby, E González Solares, A Breger, M Roberts, L Escudero Sánchez, J Babar, JHF Rudd, NA Walton, E Sala, C-B Schönlieb, JR Weir-McCall, AIX-COVNET Collaboration, members of the AIX-COVNET collaboration
– Radiology Artificial Intelligence
(2025)
e240003
(doi: 10.1148/ryai.240003)
Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis
X Chen, Y Huang, B Jessney, J Sangha, S Gu, C-B Schönlieb, M Bennett, M Roberts
(2025)
(link to publication)
Symplectic Neural Flows for Modeling and Discovery
P Canizares, D Murari, C-B Schönlieb, F Sherry, Z Shumaylov
(2024)
(link to publication)
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation
Z Deng, Y Cheng, L Liu, S Wang, R Ke, CB Schonlieb, AI Aviles-Rivero
– IEEE Transactions on Intelligent Transportation Systems
(2024)
26,
2747
(doi: 10.1109/tits.2024.3510551)
Training Data Reconstruction: Privacy due to Uncertainty?
C Runkel, KV Gandikota, J Geiping, C-B Schönlieb, M Moeller
(2024)
(link to publication)
Neural networks for the approximation of Euler's elastica
E Celledoni, E Çokaj, A Leone, S Leyendecker, D Murari, B Owren, RTSM de Almagro, M Stavole
– Computer Methods in Applied Mechanics and Engineering
(2024)
435,
117584
(doi: 10.1016/j.cma.2024.117584)
Operator learning regularization for macroscopic permeability prediction in dual-scale flow problem
C Runkel, S Xiao, N Boullé, Y Chen
(2024)
(link to publication)
PARAMETER CHOICES IN HAARPSI FOR IQA WITH MEDICAL IMAGES
A Breger, M Roberts, J Rudd, C Schoenlieb, J Weir-McCall
– Arxiv
(2024)
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios.
L Liu, Y Cheng, Z Deng, S Wang, D Chen, X Hu, P Liò, CB Schönlieb, A Aviles-Rivero
– CoRR
(2024)
abs/2311.18839,
1265
(doi: 10.1145/3664647.3681153)
Hamiltonian Matching for Symplectic Neural Integrators
P Canizares, D Murari, C-B Schönlieb, F Sherry, Z Shumaylov
(2024)
(link to publication)
Parallel-in-Time Solutions with Random Projection Neural Networks
MM Betcke, LM Kreusser, D Murari
(2024)
(link to publication)
Exploiting Pseudo-labeling and nnU-Netv2 Inference Acceleration for Abdominal Multi-organ and Pan-Cancer Segmentation
Z Huang, J Ye, H Wang, Z Deng, T Li, J He
– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
(2024)
14544 LNCS,
15
(doi: 10.1007/978-3-031-58776-4_2)
A study of why we need to reassess full reference image quality assessment with medical images
A Breger, A Biguri, MS Landman, I Selby, N Amberg, E Brunner, J Gröhl, S Hatamikia, C Karner, L Ning, S Dittmer, M Roberts, AIX-COVNET Collaboration, C-B Schönlieb
(2024)
(link to publication)
A study on the adequacy of common IQA measures for medical images
A Breger, C Karner, I Selby, J Gröhl, S Dittmer, E Lilley, J Babar, J Beckford, TR Else, TJ Sadler, S Shahipasand, A Thavakumar, M Roberts, C-B Schönlieb
– Springer Lecture Notes in Electrical Engineering, MICAD conference (2024)
(2024)
(link to publication)
Can physics-informed neural networks beat the finite element method?
TG Grossmann, UJ Komorowska, J Latz, C-B Schönlieb
– IMA Journal of Applied Mathematics (Institute of Mathematics and Its Applications)
(2024)
89,
143
(doi: 10.1093/imamat/hxae011)
Continuous Learned Primal Dual
C Runkel, A Biguri, C-B Schönlieb
(2024)
(link to publication)

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