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portrait of Dr Giacomo Tarroni

Dr Giacomo Tarroni

Lecturer in Artificial Intelligence

School of Mathematics, Computer Science and Engineering, Department of Computer Science

Contact Information


Visit Giacomo Tarroni

A302B, College Building

Postal Address

City, University of London
Northampton Square
United Kingdom



Giacomo Tarroni has been a full-time researcher in the field of medical image analysis since 2009. His work has been mainly focused on image segmentation, image registration, quality control and object tracking for cardiovascular, brain and fetal images. In particular, he obtained his Ph.D. from the University of Bologna, Italy (in collaboration with the University of Chicago, U.S.) working on the automated analysis of first-pass myocardial perfusion sequences in MRI. During his post-doc at the University of Padova, Italy, he focused on the automated analysis of fetal ultrasound images. After being awarded a Marie Skłodowska-Curie Fellowship from the European Commission, he moved to Imperial College London, where he became interested in the applications of machine learning and AI to automated organ detection, quality control assessment and motion correction for cardiac MRI.

His current research focus is on machine learning approaches for image quality assessment through outlier detection, shape analysis through representation learning and image-to-image translation through generative models, both for medical image analysis and more generally for computer vision.

Giacomo was able to generate over 183 k€ in funding from the EU by winning a Marie Skłodowska-Curie Fellowship for the project JUNO, of which he was Principal Investigator. In addition, in his career he has collaborated with several high-profile medical image analysis research projects, including SmartHeart (EPSRC, 5M£), iFind (Wellcome Trust and EPSRC , 10M£), CHIRON (EU Artemis-JU, 18M€).

Giacomo has recently been Associate Editor for the IEEE ISBI 2019 conference, and he often acts as reviewer for international journals (e.g. Plos ONE, IEEE Access, IEEE Trans Image Process) as well as renowned international conferences (e.g. MICCAI, IEEE ISBI). Since 2018 he is also board member of the UK Chapter of Marie Curie Alumni Association (MCAA-UK).

Giacomo is a member of the CitAI Research Centre.


  1. PhD, University of Bologna, Italy, Jan 2009 – Jun 2012
  2. M.S. in Electronic Engineering, University of Bologna, Italy, Sep 2005 – Oct 2008
  3. B.S. in Electronic Engineering, University of Bologna, Italy, Sep 2002 – Aug 2005


  1. Lecturer in Artificial Intelligence, City, University of London, Sep 2019 – present
  2. Research Fellow, Imperial College London, Nov 2017 – present
  3. Marie Skłodowska-Curie Fellow, Imperial College London, Nov 2015 – Nov 2017
  4. Post-doctoral Research Associate, University of Padova, Jun 2013 – Nov 2015
  5. Post-doctoral Research Associate, University of Bologna, Jul 2012 – May 2013
  6. Visiting Researcher, University of Chicago, Apr – Jul 2010


  1. Tarroni, G., Oktay, O., Sinclair, M., Bai, W., Schuh, A., Suzuki, H. … Rueckert, D. (2018). A comprehensive approach for learning-based fully-automated inter-slice motion correction for short-axis cine cardiac MR image stacks.
  2. Biffi, C., Oktay, O., Tarroni, G., Bai, W., De Marvao, A., Doumou, G. … Rueckert, D. (2018). Learning interpretable anatomical features through deep generative models: Application to cardiac remodeling.
  3. Tarroni, G., Visentin, S., Cosmi, E. and Grisan, E. (2015). Fully-automated identification and segmentation of aortic lumen from fetal ultrasound images.
  4. Tarroni, G., Oktay, O., Bai, W., Schuh, A., Suzuki, H., Passerat-Palmbach, J. … 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.
  5. Tarroni, G., Corsi, C., Antkowiak, P.F., Veronesi, F., Kramer, C.M., Epstein, F.H. … Patel, A.R. (2012). Myocardial perfusion: Near-automated evaluation from contrast-enhanced MR images obtained at rest and during vasodilator stress. Radiology, 265(2), pp. 576–583. doi:10.1148/radiol.12112475.

Conference papers and proceedings (23)

  1. Bai, W., Chen, C., Tarroni, G., Duan, J., Guitton, F., Petersen, S.E. … Rueckert, D. (2019). Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction.
  2. Bai, W., Suzuki, H., Qin, C., Tarroni, G., Oktay, O., Matthews, P.M. … Rueckert, D. (2018). Recurrent Neural Networks for Aortic Image Sequence Segmentation with Sparse Annotations.
  3. Tarroni, G., Oktay, O., Bai, W., Schuh, A., Suzuki, H., Passerat-Palmbach, J. … Rueckert, D. (2017). Learning-based heart coverage estimation for short-axis cine cardiac MR images.
  4. Bai, W., Oktay, O., Sinclair, M., Suzuki, H., Rajchl, M., Tarroni, G. … Rueckert, D. (2017). Semi-supervised learning for network-based cardiac MR image segmentation.
  5. Oktay, O., Tarroni, G., Bai, W., De Marvao, A., O'Regan, D., Cook, S. … Rueckert, D. (2016). Respiratory motion correction for 2D cine cardiac MR images using probabilistic edge maps.
  6. Tarroni, G., Visentin, S., Cosmi, E. and Grisan, E. (2015). A fully automated approach to aortic distensibility quantification from fetal ultrasound images.
  7. Tarroni, G., Visentin, S., Cosmi, E. and Grisan, E. (2015). A novel approach to aortic intima-media thickness quantification from fetal ultrasound images.
  8. Tarroni, G., Castellaro, M., Boffano, C., Bruzzone, M.G., Bertoldo, A. and Grisan, E. (2015). A novel approach to motion correction for ASL images based on brain contours.
  9. Grisan, E., Cantisani, G., Tarroni, G., Yoon, S.K. and Rossi, M. (2015). A supervised learning approach for the robust detection of heart beat in plethysmographic data.
  10. Boschetto, D., Mirzaei, H., Leong, R.W.L., Tarroni, G. and Grisan, E. (2015). Semiautomatic detection of villi in confocal endoscopy for the evaluation of celiac disease.
  11. Tarroni, G., Visentin, S., Cosmi, E. and Grisan, E. (2014). Automated estimation of aortic intima-media thickness from fetal ultrasound.
  12. Marino, M., Veronesi, F., Tarroni, G., Mor-Avi, V., Patel, A.R. and Corsi, C. (2014). Fully automated assessment of left ventricular volumes, function and mass from cardiac MRI.
  13. Tarroni, G., Visentin, S., Cosmi, E. and Grisan, E. (2014). Near-automated quantification of prenatal aortic intima-media thickness from ultrasound images.
  14. Kawaji, K., Marino, M., Tanaka, A., Tarroni, G., Ota, T., Lang, R.M. … Patel, A.R. (2014). A Novel Technique for Respiratory Motion Correction in Rapid Left Ventricular Myocardial T1 Mapping and Quantitative Analysis of Myocardial Fibrosis.
  15. Tarroni, G., Marsili, D., Veronesi, F., Corsi, C., Patel, A.R., Mor-Avi, V. … Lamberti, C. (2013). Automated MRI-based biventricular segmentation using 3D narrow-band statistical level-sets.
  16. Tarroni, G., Marsili, D., Veronesi, F., Corsi, C., Lamberti, C. and Sanguinetti, G. (2013). Near-automated 3D segmentation of left and right ventricles on magnetic resonance images.
  17. Tarroni, G., Patel, A.R., Yodwut, C., Lang, R.M., Lamberti, C., Mor-Avi, V. … Corsi, C. (2012). Automated tracking of deformable objects based on non-rigid registration of cardiac images.
  18. Corsi, C., Tarroni, G., Tornani, A., Severi, S. and Lamberti, C. (2011). Automatic quantification of cardiac scar extent from late gadolinium enhancement magnetic resonance imaging.
  19. Tarroni, G., Corsi, C., Antkowiak, P.F., Veronesi, F., Kramer, C.M., Epstein, F.H. … Mor-Avi, V. (2011). Clinical validation of an automated technique for MRI based quantification of myocardial perfusion.
  20. Caiani, E.G., Redaelli, A., Parodi, O., Votta, E., Maffessanti, F., Tripoliti, E. … Corsi, C. (2010). Development and validation of automated endocardial and epicardial contour detection for MRI volumetric and wall motion analysis.
  21. Lemmo, M., Azarine, A., Tarroni, G., Corsi, C. and Lamberti, C. (2010). Estimation of right ventricular volume, quantitative assessment of wall motion and trabeculae mass in arrhythmogenic right ventricular dysplasia.
  22. Tarroni, G., Patel, A.R., Veronesi, F., Lamberti, C., Mor-Avi, V. and Corsi, C. (2010). Feasibility of automated frame-by-frame myocardial segmentation as a basis for quantification of first-pass perfusion images.
  23. Tarroni, G., Patel, A.R., Veronesi, F., Walter, J., Lamberti, C., Lang, R.M. … Corsi, C. (2010). MRI-based quantification of myocardial perfusion at rest and stress using automated frame-by-frame segmentation and non-rigid registration.

Journal articles (12)

  1. Tarroni, G., Bai, W., Oktay, O., Schuh, A., Suzuki, H., Glocker, B. … Rueckert, D. (2020). Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank. Scientific Reports, 10(1). doi:10.1038/s41598-020-58212-2.
  2. Chen, C., Qin, C., Qiu, H., Tarroni, G., Duan, J., Bai, W. … Rueckert, D. (2020). Deep Learning for Cardiac Image Segmentation: A Review. Frontiers in Cardiovascular Medicine, 7. doi:10.3389/fcvm.2020.00025.
  3. Chen, C., Ouyang, C., Tarroni, G., Schlemper, J., Qiu, H., Bai, W. … Rueckert, D. (2020). Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation. pp. 209–219. doi:10.1007/978-3-030-39074-7_22.
  4. Biffi, C., Cerrolaza, J.J., Tarroni, G., Bai, W., Marvao, A.D., Oktay, O. … Rueckert, D. (2020). Explainable Anatomical Shape Analysis through Deep Hierarchical
    Generative Models.
    IEEE Transactions on Medical Imaging. doi:10.1109/TMI.2020.2964499.
  5. Biffi, C., Cerrolaza, J.J., Tarroni, G., 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. Proceedings - International Symposium on Biomedical Imaging, 2019-April, pp. 1643–1646. doi:10.1109/ISBI.2019.8759328.
  6. Chen, C., Biffi, C., Tarroni, G., Petersen, S., Bai, W. and Rueckert, D. (2019). Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11765 LNCS, pp. 523–531. doi:10.1007/978-3-030-32245-8_58.
  7. Bai, W., Sinclair, M., Tarroni, G., Oktay, O., Rajchl, M., Vaillant, G. … Rueckert, D. (2018). Automated cardiovascular magnetic resonance image analysis with fully convolutional networks 08 Information and Computing Sciences 0801 Artificial Intelligence and Image Processing. Journal of Cardiovascular Magnetic Resonance, 20(1). doi:10.1186/s12968-018-0471-x.
  8. Narang, A., Mor-Avi, V., Bhave, N.M., Tarroni, G., Corsi, C., Davidson, M.H. … Patel, A.R. (2016). Large high-density lipoprotein particle number is independently associated with microvascular function in patients with well-controlled low-density lipoprotein concentration: A vasodilator stress magnetic resonance perfusion study. Journal of Clinical Lipidology, 10(2), pp. 314–322. doi:10.1016/j.jacl.2015.12.006.
  9. Veronese, E., Tarroni, G., Visentin, S., Cosmi, E., Linguraru, M.G. and Grisan, E. (2014). Estimation of prenatal aorta intima-media thickness from ultrasound examination. Physics in Medicine and Biology, 59(21), pp. 6355–6371. doi:10.1088/0022-3727/59/21/6355.
  10. Tarroni, G., Tersi, L., Corsi, C. and Stagni, R. (2012). Prosthetic component segmentation with blur compensation: A fast method for 3D fluoroscopy. Medical and Biological Engineering and Computing, 50(6), pp. 631–640. doi:10.1007/s11517-012-0884-x.
  11. Conti, C.A., Votta, E., Corsi, C., de Marchi, D., Tarroni, G., Stevanella, M. … Redaelli, A. (2011). Left ventricular modelling: A quantitative functional assessment tool based on cardiac magnetic resonance imaging. Interface Focus, 1(3), pp. 384–395. doi:10.1098/rsfs.2010.0029.
  12. Rajchl, M., Lee, M.C.H., Schrans, F., Davidson, A., Passerat-Palmbach, J., Tarroni, G. … Rueckert, D. Learning under Distributed Weak Supervision. .