E-LIB Suche - Ergebnisse für: Pinnock, Mark

1

Time conditioning for arbitrary contrast phase generation i..:

Pinnock, Mark A ; Hu, Yipeng ; Bandula, Steve.
Physics in Medicine & Biology. 69 (2024) 11 - p. 115010 , 2024

Link: https://doi.org/10.1088/..

2

Active learning using adaptable task-based prioritisation:

Saeed, Shaheer U. ; Ramalhinho, João ; Pinnock, Mark...
Medical Image Analysis. 95 (2024) - p. 103181 , 2024

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

3

Multi-phase synthetic contrast enhancement in interventiona..:

Pinnock, Mark A. ; Hu, Yipeng ; Bandula, Steve.
International Journal of Computer Assisted Radiology and Surgery. 18 (2023) 8 - p. 1437-1449 , 2023

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

4

Imaging features for the prediction of clinical endpoints i..:

Chouhan, Manil D ; Taylor, Stuart Andrew ; Bhagwanani, Anisha...
BMJ Open. 12 (2022) 5 - p. e053204 , 2022

Link: https://doi.org/10.1136/..

5

Prostate Motion Modelling Using Biomechanically-Trained Dee..:

, In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020; Lecture Notes in Computer Science,

Saeed, Shaheer U. ; Taylor, Zeike A. ; Pinnock, Mark A.... - p. 650-659 , 2020

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

6

Multimodal Healthcare AI: Identifying and Designing Clinica..:

, In: Proceedings of the CHI Conference on Human Factors in Computing Systems,

Yildirim, Nur ; Richardson, Hannah ; Wetscherek, Maria Teodora... - p. 1-22 , 2024

Link: https://dl.acm.org/doi/1..

7

Multi-phase synthetic contrast enhancement in interventiona..:

Pinnock, Mark A ; Hu, Yipeng ; Bandula, Steve.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10363071/. , 2023

Link: http://www.ncbi.nlm.nih...

8

Multi-phase synthetic contrast enhancement in interventiona..:

Pinnock, Mark A ; Hu, Yipeng ; Bandula, Steve.
https://discovery.ucl.ac.uk/id/eprint/10165327/1/s11548-023-02843-z.pdf. , 2023

Link: https://discovery.ucl.ac..

9

Active learning using adaptable task-based prioritisation:

Saeed, Shaheer U ; Ramalhinho, João ; Pinnock, Mark...
http://arxiv.org/abs/2212.01703. , 2022

Link: http://arxiv.org/abs/221..

10

Imaging features for the prediction of clinical endpoints i..:

Chouhan, Manil D ; Taylor, Stuart Andrew ; Bhagwanani, Anisha...
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9062789/. , 2022

Link: http://www.ncbi.nlm.nih...

11

Imaging features for the prediction of clinical endpoints i..:

Chouhan, Manil D ; Taylor, Stuart Andrew ; Bhagwanani, Anisha...
https://discovery.ucl.ac.uk/id/eprint/10148169/1/Chouhan_Imaging%20features%20for%20the%20prediction%20of%20clinical%20endpoints%20in%20chronic%20liver%20disease_VoR.pdf. , 2022

Link: https://discovery.ucl.ac..

12

Deep learning-based detection of liver disease using MRI:

Pinnock, Mark A ; Hu, Yipeng ; Bainbridge, Alan...
https://discovery.ucl.ac.uk/id/eprint/10178914/1/2988.pdf. , 2021

Link: https://discovery.ucl.ac..

13

Prostate motion modelling using biomechanically-trained dee..:

Saeed, Shaheer U ; Taylor, Zeike A ; Pinnock, Mark A...
http://arxiv.org/abs/2007.04972. , 2020

Link: http://arxiv.org/abs/200..

14

Imaging features for the prediction of clinical endpoints i..:

Rajeshwar P Mookerjee ; Steve Halligan ; Dominic Yu...
https://bmjopen.bmj.com/content/12/5/e053204.full. , 2022

Link: https://doi.org/10.1136/..

15

ERS "CONNECT" Clinical Research Collaboration – moving mult..:

van Boven, Job F.M. ; Drummond, David ; Chan, Amy H.Y....
European Respiratory Journal. 62 (2023) 5 - p. 2301680 , 2023

Link: https://doi.org/10.1183/..