King's College London

Research portal

Research Outputs

  1. 2017
  2. McDonagh S, Hou B, Alansary A, Oktay O, Kamnitsas K, Rutherford M et al. Context-sensitive super-resolution for fast fetal magnetic resonance imaging. In Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment - 5th International Workshop, CMMI 2017 2nd International Workshop, RAMBO 2017 and 1st International Workshop, SWITCH 2017 Held in Conjunction with MICCAI 2017, Proceedings. Vol. 10555 LNCS. Springer Verlag. 2017. p. 116-126. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-67564-0_12
  3. Hou B, Alansary A, McDonagh S, Davidson A, Rutherford M, Hajnal JV et al. Predicting slice-to-volume transformation in presence of arbitrary subject motion. In Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings. Vol. 10434 LNCS. Springer Verlag. 2017. p. 296-304. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-66185-8_34
  4. Schuh A, Makropoulos A, Wright R, Robinson EC, Tusor N, Steinweg J et al. A deformable model for the reconstruction of the neonatal cortex. In 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017. IEEE Computer Society. 2017. p. 800-803 https://doi.org/10.1109/ISBI.2017.7950639
  5. Abo Seada S, Hajnal JV, Malik SJ. A simple optimisation approach to making time efficient VERSE-multiband pulses feasible on non-ideal gradients. In A simple optimisation approach to making time efficient VERSE-multiband pulses feasible on non-ideal gradients. 2017. 5059
  6. Abo Seada S, Hajnal JV, Malik SJ. Root-flipped multiband pulses with inherently aligned echoes. In Root-flipped multiband pulses with inherently aligned echoes. 2017. 3955
  7. Rajchl M, Lee MCH, Oktay O, Kamnitsas K, Passerat-Palmbach J, Bai W et al. DeepCut: Object Segmentation from Bounding Box Annotations Using Convolutional Neural Networks. IEEE Transactions on Medical Imaging. 2017 Feb 1;36(2):674-683. 7739993. https://doi.org/10.1109/TMI.2016.2621185
  8. Schlemper J, Caballero J, Hajnal JV, Price A, Rueckert D. A deep cascade of convolutional neural networks for MR image reconstruction. In Information Processing in Medical Imaging - 25th International Conference, IPMI 2017, Proceedings. Vol. 10265 LNCS. Springer Verlag. 2017. p. 647-658. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-59050-9_51
  9. 2016
  10. Zhang T, Matthew J, Lohezic M, Davidson A, Rutherford MA, Rueckert D et al. Graph-based whole body segmentation in fetal MR images. In MICCAI Workshop on Perinatal, Preterm and Paediatric Image analysis 2016. 2016
Previous 1 2 3 4 5 6 7 8 ...13 Next

Export:RIS BibTex Word PDF - will at most contain 500 items

Refine results Clear filters

Language

Language

Publication year

Full text

Full text

Meeting and poster abstracts

Authors

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454