Cian Scannell

2024

Automated cardiovascular MR myocardial scar quantification with unsupervised domain adaptation

Crawley, R., Amirrajab, S., Lustermans, D., Holtackers, R. J., Plein, S., Veta, M., Breeuwer, M., Chiribiri, A. & Scannell, C. M., 14 Aug 2024, In: European radiology experimental. 8, 1, p. 93 93.

Research output: Contribution to journal › Article › peer-review

Open Access

Automated inversion time selection for late gadolinium-enhanced cardiac magnetic resonance imaging

Xie, C., Zhang, R., Mensink, S., Gandharva, R., Awni, M., Lim, H., Kachel, S. E., Cheung, E., Crawley, R., Churilov, L., Bettencourt, N., Chiribiri, A., Scannell, C. M. & Lim, R. P., Sept 2024, In: European Radiology. 34, 9, p. 5816-5828 13 p.

Research output: Contribution to journal › Article › peer-review

Open Access

1 Citation (Scopus)

Deep Learning Synthesis of White-Blood From Dark-Blood Late Gadolinium Enhancement Cardiac Magnetic Resonance

Jaspers, T. J. M., Martens, B., Crawley, R., Jada, L., Amirrajab, S., Breeuwer, M., Holtackers, R. J., Chiribiri, A. & Scannell, C. M., 1 Nov 2024, In: Investigative Radiology. 59, 11, p. 767-773 7 p.

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

High-Resolution Free-Breathing Automated Quantitative Myocardial Perfusion by Cardiovascular Magnetic Resonance for the Detection of Functionally Significant Coronary Artery Disease

Crawley, R., Kunze, K. P., Milidonis, X., Highton, J., McElroy, S., Frey, S. M., Hoefler, D., Karamanli, C., Wong, N. C. K., Backhaus, S. J., Alskaf, E., Neji, R., Scannell, C. M., Plein, S. & Chiribiri, A., 1 Jul 2024, In: European heart journal. Cardiovascular Imaging. 25, 7, p. 914-925 12 p.

Research output: Contribution to journal › Article › peer-review

Open Access

1 Citation (Scopus)

Hybrid artificial intelligence outcome prediction using features extraction from stress perfusion cardiac magnetic resonance images and electronic health records

Alskaf, E., Crawley, R., Scannell, C. M., Suinesiaputra, A., Young, A., Masci, P-G., Perera, D. & Chiribiri, A., 30 Mar 2024, In: Journal of Medical Artificial Intelligence. 7, p. 3 3.

Research output: Contribution to journal › Article › peer-review

Open Access

Machine learning outcome prediction using stress perfusion cardiac magnetic resonance reports and natural language processing of electronic health records

Alskaf, E., Frey, S. M., Scannell, C. M., Suinesiaputra, A., Vilic, D., Dinu, V., Masci, P. G., Perera, D., Young, A. & Chiribiri, A., Jan 2024, In: Informatics in Medicine Unlocked. 44, 101418.

Research output: Contribution to journal › Article › peer-review

Open Access

1 Citation (Scopus)

Qualitative stress perfusion American Heart Association plot and outcome prediction using artificial intelligence

Alskaf, E., Scannell, C. M., Crawley, R., Suinesiaputra, A., Masci, P. G., Young, A., Perera, D. & Chiribiri, A., Jan 2024, In: Informatics in Medicine Unlocked. 49, 101537.

Research output: Contribution to journal › Article › peer-review

Open Access

Qualitative stress perfusion American Heart Association plot and outcome prediction using artificial intelligence

Alskaf, E., Scannell, C. M., Crawley, R., Suinesiaputra, A., Masci, P., Young, A., Perera, D. & Chiribiri, A., Jan 2024, In: Informatics in Medicine Unlocked. 49, p. 101537 101537.

Research output: Contribution to journal › Article › peer-review

Open Access

2023

Corrigendum to “Machine learning outcome prediction using stress perfusion cardiac magnetic resonance reports and natural language processing of electronic health records” [Inform. Med. Unlocked (2024) 1–7/101418] (Informatics in Medicine Unlocked (2024) 44, (S2352914823002642), (10.1016/j.imu.2023.101418))

Alskaf, E., Frey, S. M., Scannell, C. M., Suinesiaputra, A., Vilic, D., Dinu, V., Masci, P. G., Perera, D., Young, A. & Chiribiri, A., 2023, (Accepted/In press) In: Informatics in Medicine Unlocked. 101431.

Research output: Contribution to journal › Comment/debate › peer-review

Open Access

2022

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 journal › Article › peer-review

Open Access

9 Citations (Scopus)

Deep learning applications in coronary anatomy imaging: a systematic review and meta-analysis

Alskaf, E., Dutta, U., Scannell, C. M. & Chiribiri, A., 30 Dec 2022, In: Journal of Medical Artificial Intelligence. 5, 11.

Research output: Contribution to journal › Article › peer-review

Open Access

2 Citations (Scopus)

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 journal › Article › peer-review

Open Access

8 Citations (Scopus)

Optimized automated cardiac MR scar quantification with GAN-based data augmentation

Lustermans, D. R. P. R. M., Amirrajab, S., Veta, M., Breeuwer, M. & Scannell, C. M., Nov 2022, In: Computer methods and programs in biomedicine. 226, 107116.

Research output: Contribution to journal › Article › peer-review

Open Access

12 Citations (Scopus)

2021

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 proceeding › Conference paper › peer-review

6 Citations (Scopus)

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 journal › Article › peer-review

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 proceeding › Conference paper › peer-review

Open Access

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17 Citations (Scopus)

80 Downloads (Pure)

High-Resolution Cardiac Magnetic Resonance Imaging Techniques for the Identification of Coronary Microvascular Dysfunction

Rahman, H., Scannell, C. M., Demir, O. M., Ryan, M., McConkey, H., Ellis, H., Masci, P. G., Perera, D. & Chiribiri, A., 3 May 2021, In: JACC. Cardiovascular imaging.

Research output: Contribution to journal › Article › peer-review

Open Access

78 Citations (Scopus)

14 Downloads (Pure)

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 journal › Article › peer-review

Open Access