Items where City Author is "Tarroni, Giacomo"
Guizzo, E., Weyde, T. ORCID: 0000-0001-8028-9905, Tarroni, G.
ORCID: 0000-0002-0341-6138 & Comminiello, D. (2023).
Quaternion Anti-Transfer Learning for Speech Emotion Recognition.
2023 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA),
ISSN 1931-1168
doi: 10.1109/WASPAA58266.2023.10248082
van de Venter, R., Skelton, E. ORCID: 0000-0003-0132-7948, Matthew, J. , Woznitza, N., Tarroni, G.
ORCID: 0000-0002-0341-6138, Hirani, S. P.
ORCID: 0000-0002-1577-8806, Kumar, A., Malik, R. & Malamateniou, C.
ORCID: 0000-0002-2352-8575 (2023).
Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study.
Insights Imaging, 14(1),
25.
doi: 10.1186/s13244-023-01372-2
Chen, C., Qin, C., Ouyang, C. , Li, Z., Wang, S., Qiu, H., Chen, L., Tarroni, G. ORCID: 0000-0002-0341-6138, Bai, W. & Rueckert, D. (2022).
Enhancing MR image segmentation with realistic adversarial data augmentation.
Medical Image Analysis, 82,
102597.
doi: 10.1016/j.media.2022.102597
Marimont, S. N. & Tarroni, G. ORCID: 0000-0002-0341-6138 (2022).
Implicit U-Net for Volumetric Medical Image Segmentation.
Paper presented at the Medical Image Understanding and Analysis 26th Annual Conference, MIUA 2022, 27-29 Jul 2022, Cambridge, UK.
doi: 10.1007/978-3-031-12053-4_29
Zimmerer, D., Full, P. M, Isensee, F. , Jäger, P., Adler, T., Petersen, J., Kohler, G., Ross, T., Reinke, A., Kascenas, A., Jensen, B. S., O'Neil, A. Q., Tan, J., Hou, B., Batten, J., Qiu, H., Kainz, B., Shvetsova, N., Fedulova, I., Dylov, D. V., Yu, B., Zhai, J., Hu, J., Si, R., Zhou, S., Wang, S., Li, X., Chen, X., Zhao, Y., Marimont, S. N., Tarroni, G. ORCID: 0000-0002-0341-6138, Saase, V., Maier-Hein, L. & Maier-Hein, K. (2022).
MOOD 2020: A public Benchmark for Out-of-Distribution Detection and Localization on medical Images.
IEEE Transactions on Medical Imaging, 41(10),
pp. 2728-2738.
doi: 10.1109/TMI.2022.3170077
Naval Marimont, S. & Tarroni, G. (2021). Implicit Field Learning for Unsupervised Anomaly Detection in Medical Images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12902, pp. 189-198. doi: 10.1007/978-3-030-87196-3_18
Marimont, S. N. & Tarroni, G. ORCID: 0000-0002-0341-6138 (2021).
Implicit field learning for unsupervised anomaly detection in medical images.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021.
Lecture Notes in Computer Science, 12902.
. UNSPECIFIED.
ISBN 978-3-030-87195-6
doi: 10.1007/978-3-030-87196-3_18
Marimont, S. N. & Tarroni, G. ORCID: 0000-0002-0341-6138 (2021).
Anomaly detection through latent space restoration using vector-quantized variational autoencoders.
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI),
ISSN 1945-7928
doi: 10.1109/ISBI48211.2021.9433778
Guizzo, E., Weyde, T. ORCID: 0000-0001-8028-9905 & Tarroni, G.
ORCID: 0000-0002-0341-6138 (2021).
Anti-transfer learning for task invariance in convolutional neural networks for speech processing.
Neural Networks, 142,
pp. 238-251.
doi: 10.1016/j.neunet.2021.05.012
Bai, W., Suzuki, H., Huang, J. , Francis, C., Wang, S., Tarroni, G. ORCID: 0000-0002-0341-6138, Guitton, F., Aung, N., Fung, K., Petersen, S. E., Piechnik, S. K., Neubauer, S., Evangelou, E., Dehghan, A., O'Regan, D., Wilkinson, M., Guo, Y., Matthews, P. M. & Rueckert, D. (2020).
A population-based phenome-wide association study of cardiac and aortic structure and function.
Nature Medicine, 26(10),
pp. 1654-1662.
doi: 10.1038/s41591-020-1009-y
Wang, S., Tarroni, G. ORCID: 0000-0002-0341-6138, Qin, C. , Mo, Y., Dai, C., Chen, C., Glocker, B., Guo, Y., Rueckert, D. & Bai, W. (2020).
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020.
Lecture Notes in Computer Science.
(pp. 88-97). UNSPECIFIED.
ISBN 978-3-030-59718-4
doi: 10.1007/978-3-030-59719-1_9
Chen, C., Qin, C., Qiu, H. , Ouyang, C., Wang, S., Chen, L., Tarroni, G. ORCID: 0000-0002-0341-6138, Bai, W. & Rueckert, D. (2020).
Realistic Adversarial Data Augmentation for MR Image Segmentation.
Paper presented at the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, 04 - 08 October 2020, Lima, Peru.
doi: 10.1007/978-3-030-59710-8_65
Biffi, C., Cerrolaza, J. J., Tarroni, G. ORCID: 0000-0002-0341-6138 , Bai, W., Marvao, A. de, Oktay, O., Ledig, C., Folgoc, L. L., Kamnitsas, K., Doumou, G., Duan, J., Prasad, S. K., Cook, S. A., O'Regan, D. P. & Rueckert, D. (2020).
Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models.
IEEE Transactions on Medical Imaging, 39(6),
pp. 2088-2099.
doi: 10.1109/TMI.2020.2964499
Tarroni, G. ORCID: 0000-0002-0341-6138, Bai, W., Oktay, O. , Schuh, A., Suzuki, H., Glocker, B., Matthews, P. M. & Rueckert, D. (2020).
Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank.
Scientific Reports, 10(1),
2408.
doi: 10.1038/s41598-020-58212-2
Rajchl, M., Lee, M., Schrans, F. , Davidson, A., Passerat-Palmbach, J., Tarroni, G. ORCID: 0000-0002-0341-6138, Alansary, A., Oktay, O., Kainz, B. & Rueckert, D. (2020).
Learning under Distributed Weak Supervision.
.
Chen, C., Ouyang, C., Tarroni, G. ORCID: 0000-0002-0341-6138 , Schlemper, J., Qiu, H., Bai, W. & Rueckert, D. (2020).
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation.
In: Pop, M., Sermesant, M., Camara, O. , Zhuang, X., Li, S., Young, A., Mansi, T. & Suinesiaputra, A. (Eds.),
Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges. STACOM 2019.
(pp. 209-219). Cham, Switzerland: Springer.
ISBN 978-3-030-39073-0
doi: 10.1007/978-3-030-39074-7_22
Bai, W., Chen, C., Tarroni, G. ORCID: 0000-0002-0341-6138 , Duan, J., Guitton, F., Petersen, S. E., Guo, Y., Matthews, P. M. & Rueckert, D. (2019).
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction.
In: Shen, D., Liu, T., Peters, T. M. , Staib, L. H., Essert, C., Zhou, S., Yap, P-T. & Khan, A. (Eds.),
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. Lecture Notes in Computer Science, vol 11765.
(pp. 541-549). Cham: Springer.
ISBN 9783030322441
Biffi, C., Cerrolaza, J. J., Tarroni, G. ORCID: 0000-0002-0341-6138 , de Marvao, A., Cook, S. A., O'Regan, D. P. & Rueckert, D. (2019).
3D High-Resolution Cardiac Segmentation Reconstruction From 2D Views Using Conditional Variational Autoencoders.
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019,
pp. 1643-1646.
doi: 10.1109/ISBI.2019.8759328
Tarroni, G. ORCID: 0000-0002-0341-6138, Oktay, O., Bai, W. , Schuh, A., Suzuki, H., Passerat-Palmbach, J., De Marvao, A., O’Regan, D. P., Cook, S., Glocker, B., Matthews, P M. & Rueckert, D. (2019).
Learning-based quality control for cardiac MR images.
IEEE Transactions on Medical Imaging, 38(5),
pp. 1127-1138.
doi: 10.1109/TMI.2018.2878509
Chen, C., Qin, C., Qiu, H. , Tarroni, G. ORCID: 0000-0002-0341-6138, Duan, J., Bai, W. & Rueckert, D. (2019).
Deep learning for cardiac image segmentation: A review.
City, university of London.
Tarroni, G. ORCID: 0000-0002-0341-6138, Oktay, O., Sinclair, M. , Bai, W., Schuh, A., Suzuki, H., de Marvao, A., O'Regan, D., Cook, S. & Rueckert, D. (2018).
A Comprehensive Approach for Learning-Based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018.
Lecture Notes in Computer Science, 11070.
(pp. 268-276). Cham: Springer.
ISBN 978-3-030-00927-4
doi: 10.1007/978-3-030-00928-1_31
Biffi, C., Oktay, O., Tarroni, G. ORCID: 0000-0002-0341-6138 , De Marvao, A., Bai, W., Doumou, G., Rajchl, M., Bedair, R., Prasad, S., Cook, S., O'Regan, D. & Rueckert, D. (2018).
Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018. MICCAI 2018.
Lecture Notes in Computer Science, 11071.
(pp. 464-471). Cham: Springer.
ISBN 978-3-030-00933-5
doi: 10.1007/978-3-030-00934-2_52
Bai, W., Sinclair, M., Tarroni, G. ORCID: 0000-0002-0341-6138 , Oktay, O., Rajchl, M., Vaillant, G., Lee, A. M., Aung, N., Lukaschuk, E., Sanghvi, M. M., Zemrak, F., Fung, K., Paiva, J. M., Carapella, V., Kim, Y. J., Suzuki, H., Kainz, B., Matthews, P M., Petersen, S. E., Piechnik, S. K., Neubauer, S., Glocker, B. & Rueckert, D. (2018).
Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.
Journal of Cardiovascular Magnetic Resonanc, 20,
65.
doi: 10.1186/s12968-018-0471-x
Bai, W., Suzuki, H., Qin, C. , Tarroni, G. ORCID: 0000-0002-0341-6138, Oktay, O., Matthews, P. M. & Rueckert, D. (2018).
Recurrent Neural Networks for Aortic Image Sequence Segmentation with Sparse Annotations.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018.
Lecture Notes in Computer Science, 11073.
(pp. 586-594). Cham: Springer.
ISBN 978-3-030-00936-6
doi: 10.1007/978-3-030-00937-3_67