King's College London

Research portal

Mr Cian Scannell

  1. Brief Research Report: Quantitative Analysis of Potential Coronary Microvascular Disease in Suspected Long-COVID Syndrome

    Doeblin, P., Steinbeis, F., Scannell, C. M., Goetze, C., Al-Tabatabaee, S., Erley, J., Faragli, A., Pröpper, F., Witzenrath, M., Zoller, T., Stehning, C., Gerhardt, H., Sánchez-González, J., Alskaf, E., Kühne, T., Pieske, B., Tschöpe, C., Chiribiri, A. & Kelle, S., 31 May 2022, In: Frontiers in Cardiovascular Medicine. 9, p. 877416 877416.

    Research output: Contribution to journalArticlepeer-review

  2. Deep learning applications in myocardial perfusion imaging, a systematic review and meta-analysis

    Alskaf, E., Dutta, U., Scannell, C. M. & Chiribiri, A., Jan 2022, In: Informatics in Medicine Unlocked. 32, 101055.

    Research output: Contribution to journalArticlepeer-review

  3. Cardiac magnetic resonance perfusion abnormality due to anaemia

    Demir, O. M., Scannell, C. M., Chiribiri, A., Plein, S. & Perera, D., 25 Nov 2021, (E-pub ahead of print) In: European Heart Journal-Cardiovascular Imaging.

    Research output: Contribution to journalArticlepeer-review

  4. Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge

    Campello, V. M., Gkontra, P., Izquierdo, C., Martín-Isla, C., Sojoudi, A., Full, P. M., Maier-Hein, K., Zhang, Y., He, Z., Ma, J., Parreño, M., Albiol, A., Kong, F., Shadden, S. C., Acero, J. C., Sundaresan, V., Saber, M., Elattar, M., Li, H., Menze, B., & 27 othersKhader, F., Haarburger, C., Scannell, C. M., Veta, M., Carscadden, A., Punithakumar, K., Liu, X., Tsaftaris, S. A., Huang, X., Yang, X., Li, L., Zhuang, X., Viladés, D., Descalzo, M. L., Guala, A., La Mura, L., Friedrich, M. G., Garg, R., Lebel, J., Henriques, F., Karakas, M., Çavuş, E., Petersen, S. E., Escalera, S., Seguí, S., Palomares, J. F. R. & Lekadir, K., 17 Jun 2021, In: IEEE Transactions on Medical Imaging. 40, 12, p. 3543-3554 12 p.

    Research output: Contribution to journalArticlepeer-review

  5. Automatic Myocardial Disease Prediction from Delayed-Enhancement Cardiac MRI and Clinical Information

    Lourenço, A., Kerfoot, E., Grigorescu, I., Scannell, C. M., Varela, M. & Correia, T. M., 2021, Statistical Atlases and Computational Models of the Heart. MandMs and EMIDEC Challenges - 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers. Puyol Anton, E., Pop, M., Sermesant, M., Campello, V., Lalande, A., Lekadir, K., Suinesiaputra, A., Camara, O. & Young, A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 334-341 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12592 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

  6. Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation

    Scannell, C. M., Chiribiri, A. & Veta, M., 2021, Statistical Atlases and Computational Models of the Heart. MandMs and EMIDEC Challenges - 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers. Puyol Anton, E., Pop, M., Sermesant, M., Campello, V., Lalande, A., Lekadir, K., Suinesiaputra, A., Camara, O. & Young, A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 228-237 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12592 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

  7. Feasibility of free-breathing quantitative myocardial perfusion using multi-echo Dixon magnetic resonance imaging

    Scannell, C., Matias Correia, T., Villa, A., Schneider, T., Lee, J., Breeuwer, M., Chiribiri, A. & Henningsson, M., 29 Jul 2020, In: Scientific Reports. 10, 12684 .

    Research output: Contribution to journalArticlepeer-review

  8. Deep‐Learning‐Based Preprocessing for Quantitative Myocardial Perfusion MRI

    Scannell, C. M., Veta, M., Villa, A. D. M., Sammut, E. C., Lee, J., Breeuwer, M. & Chiribiri, A., 1 Jun 2020, In: Journal of Magnetic Resonance Imaging. 51, 6, p. 1689-1696 8 p.

    Research output: Contribution to journalArticlepeer-review

  9. Hierarchical Bayesian myocardial perfusion quantification

    Scannell, C. M., Chiribiri, A., Villa, A. D. M., Breeuwer, M. & Lee, J., 1 Feb 2020, In: Medical Image Analysis. 60, 101611.

    Research output: Contribution to journalArticlepeer-review

  10. Robust non-rigid motion compensation of free-breathing myocardial perfusion MRI data

    Scannell, C. M., Villa, A., Lee, C. J., Breeuwer, M. & Chiribiri, A., 1 Aug 2019, In: IEEE Transactions on Medical Imaging. 38, 8, p. 1812-1820 9 p., 8632981.

    Research output: Contribution to journalArticlepeer-review

  11. Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI

    Scannell, C. M., van den Bosch, P., Chiribiri, A., Lee, C. J., Breeuwer, M. & Veta, M., 29 Jul 2019, Medical Imaging with Deep Learning: MIDL 2019.

    Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

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