E-LIB Suche - Ergebnisse für: Scannell, Cian M.

1

Qualitative stress perfusion American Heart Association plo..:

Alskaf, Ebraham ; Scannell, Cian M. ; Crawley, Richard...
Informatics in Medicine Unlocked. 49 (2024) - p. 101537 , 2024

Link: https://doi.org/10.1016/..

2

The intelligent imaging revolution: artificial intelligence..:

Küstner, Thomas ; Qin, Chen ; Sun, Changyu..
Magnetic Resonance Materials in Physics, Biology and Medicine. , 2024

Link: https://doi.org/10.1007/..

3

Machine learning outcome prediction using stress perfusion ..:

Alskaf, Ebraham ; Frey, Simon M. ; Scannell, Cian M....
Informatics in Medicine Unlocked. 44 (2024) - p. 101418 , 2024

Link: https://doi.org/10.1016/..

4

High-resolution quantification of stress perfusion defects ..:

Scannell, Cian M ; Crawley, Richard ; Alskaf, Ebraham...
European Heart Journal - Imaging Methods and Practice. 2 (2024) 1 - p. , 2024

Link: https://doi.org/10.1093/..

5

Automated inversion time selection for late gadolinium–enha..:

Xie, Cheng ; Zhang, Rory ; Mensink, Sebastian...
European Radiology. , 2024

Link: https://doi.org/10.1007/..

6

Corrigendum to "Machine learning outcome prediction using s..:

Alskaf, Ebraham ; Frey, Simon M. ; Scannell, Cian M....
Informatics in Medicine Unlocked. 45 (2024) - p. 101431 , 2024

Link: https://doi.org/10.1016/..

7

Artificial intelligence: The next frontier of perfusion ima..:

, In: Advances in Magnetic Resonance Technology and Applications; Quantitative Perfusion MRI - Techniques, Applications and Practical Considerations,

Scannell, Cian M. ; Chiribiri, Amedeo ; Leiner, Tim - p. 291-311 , 2023

Link: https://doi.org/10.1016/..

8

Cardiac MR Image Segmentation and Quality Control in the Pr..:

, In: Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers; Lecture Notes in Computer Science,

Amirrajab, Sina ; Al Khalil, Yasmina ; Pluim, Josien.. - p. 466-475 , 2022

Link: https://doi.org/10.1007/..

9

Optimized automated cardiac MR scar quantification with GAN..:

Lustermans, Didier R.P.R.M. ; Amirrajab, Sina ; Veta, Mitko..
Computer Methods and Programs in Biomedicine. 226 (2022) - p. 107116 , 2022

Link: https://doi.org/10.1016/..

10

Deep learning applications in myocardial perfusion imaging,..:

Alskaf, Ebraham ; Dutta, Utkarsh ; Scannell, Cian M..
Informatics in Medicine Unlocked. 32 (2022) - p. 101055 , 2022

Link: https://doi.org/10.1016/..

11

AI-AIF: artificial intelligence-based arterial input functi..:

Scannell, Cian M ; Alskaf, Ebraham ; Sharrack, Noor...
European Heart Journal - Digital Health. 4 (2022) 1 - p. 12-21 , 2022

Link: https://doi.org/10.1093/..

12

High-Resolution Free-Breathing Quantitative First-Pass Perf..:

Tourais, Joao ; Scannell, Cian M. ; Schneider, Torben...
Frontiers in Cardiovascular Medicine. 9 (2022) - p. , 2022

Link: https://doi.org/10.3389/..

13

CardiSort: a convolutional neural network for cross vendor ..:

Lim, Ruth P. ; Kachel, Stefan ; Villa, Adriana D. M....
European Radiology. 32 (2022) 9 - p. 5907-5920 , 2022

Link: https://doi.org/10.1007/..

14

Brief Research Report: Quantitative Analysis of Potential C..:

Doeblin, Patrick ; Steinbeis, Fridolin ; Scannell, Cian M....
Frontiers in Cardiovascular Medicine. 9 (2022) - p. , 2022

Link: https://doi.org/10.3389/..

15

Physics-informed neural networks for myocardial perfusion M..:

van Herten, Rudolf L.M. ; Chiribiri, Amedeo ; Breeuwer, Marcel..
Medical Image Analysis. 78 (2022) - p. 102399 , 2022

Link: https://doi.org/10.1016/..