MOTION MODELLING & ANALYSIS GROUP
Artificial Intelligence for Medical Image Analysis
About us
The Motion Modelling and Analysis Group (MMAG) is an academic research group based within the School of Biomedical Engineering and Imaging Sciences of King's College London. The group is based at St. Thomas' Hospital in central London. The MMAG includes researchers from a diverse range of backgrounds and is proud to foster an inclusive research environment to allow all to thrive and reach their potential.
The MMAG has worked in the past on the imaging, modelling and estimation of repetitive motion. Currently, the group works more widely on the use of artificial intelligence (specifically machine and deep learning) for the analysis of imaging data with the aim of extracting clinically useful information. Cardiology is one of the main application areas but the group is also involved in developing machine learning solutions for other clinical application areas, such as radiotherapy and vocal tract imaging. The aim is to develop novel but clinically-driven machine learning solutions and translate them into equitable patient benefit.
Latest news
10 March 2025: Read the press release about Tiarna Lee's important research into investigating the causes of race bias in AI-based CMR analysis.
4 March 2025: Watch this video about Maram Alqarni's scholarship journey as one of the first female biomedical engineering PhD students from Saudia Arabia.
27 February 2025: New journal paper by Tiarna Lee now available:
T. Lee, E. Puyol-Antón, B. Ruijsink, S. Roujol, T. Barfoot, S. Ogbomo-Harmitt, M. Shi, A. P. King, "An Investigation Into the Causes of Race Bias in AI-based Cine CMR Segmentation", European Heart Journal Digital Health, 2025. (paper)
4 February 2025: Tareen Dawood's PhD thesis is now available online!
T. Dawood, "Improving Uncertainty Calibration of Artificial Intelligence Classification Models in Cardiology", PhD thesis, King's College London, 2024. (thesis)
19 November 2024: PhD position available in Fairness in Cardiac Digital Twins. Deadline 3rd January 2025 for an October 2025 start. This project is available through the Digital Twins for Healthcare Centre for Doctoral Training. Full scholarships available for 3.5 years with some places for international students. Project details can be found here and details of how to apply can be found here.
13 October 2024: New journal paper by Laia Humbert-Vidan now available:
L. Humbert-Vidan, V. Patel, A. P. King, T. Guerrero-Urbano, "Comparison of Deep-learning Multimodality Data Fusion Strategies in Mandibular Osteoradionecrosis NTCP Modelling Using Clinical Variables and Radiation Dose Distribution Volumes", Physics in Medicine and Biology, 2024. (paper)
25 September 2024: PhD position available in Fair and Generalisable AI for Skin Lesion Diagnosis. This fully-funded PhD is for an October 2025 start and applications should be made through the MRC Doctoral Training Programme (MRC DTP) at King's College London. The application deadline is 29 October. Details of how to apply can be found here.
29 August 2024: Check out Andrew King's talk on "Bias and Fairness in AI for Medical Imaging" from the RISE-MICCAI/FAIMI Summer School, 2024.
17 February 2024: PhD position available on Fairness in Brain MR Image Analysis. This 4-year scholarship is available through the King's College London DRIVE-Health CDT. See the DRIVE-Health web site for project details (Project #88) and entry requirements/how to apply. Application deadline: Sunday 10th March at 23:59 GMT.
2 January 2024: New blog post on the future for Fair AI by Andrew King.
2 December 2023: New journal paper and speech MRI dataset released by Matthieu Ruthven:
M. Ruthven, A. M. Peplinski, D. M. Adams, A. P. King, M. E. Miquel, "Real-time Speech MRI Datasets With Corresponding Articulator Ground-truth Segmentations", Scientific Data, 2023. (paper)
3 October 2023: New journal paper by Ines Machado now available:
I. Machado, E. Puyol-Antón, K. Hammernik, G. Cruz, D. Ugurlu, I. Olakorede, I. Oksuz, B. Ruijsink, M. Castelo-Branco, A. Young, C. Prieto, J. Schnabel, A. P. King, "A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis", IEEE Transactions on Biomedical Engineering, 2023. (paper)
2 October 2023: New Arxiv papers available for three papers to be presented at the MICCAI Workshop on Fairness of AI in Medical Imaging (FAIMI):
M. Huti, T. Lee, E. Sawyer, A. P. King, "An Investigation Into Race Bias in Random Forest Models Based on Breast DCE-MRI Derived Radiomics Features", Proceedings MICCAI FAIMI, 2023. (Arxiv paper)
C. I. Bercea, E. Puyol-Antón, B. Wiestler, D. Rueckert, J. A. Schnabel, A. P. King, "Bias in Unsupervised Anomaly Detection in Brain MRI", Proceedings MICCAI FAIMI, 2023. (Arxiv paper)
T. Lee, E. Puyol-Antón, B. Ruijsink, K. Aitcheson, M. Shi, A. P. King, "An Investigation Into the Impact of Deep Learning Model Choice on Sex and Race Bias in Cardiac MR Segmentation", Proceedings MICCAI FAIMI, 2023. (Arxiv paper)
7 August 2023: New section on this web site on Talks given by group members!
21 July 2023: New journal paper by Jorge Mariscal-Harana now available online:
J. Mariscal-Harana, C. Asher, V. Vergani, M. Rizvi, L. Keehn, R. J. Kim, R. M. Judd, S. E. Petersen, R. Razavi, A. P. King, B. Ruijsink, E. Puyol-Antón, "An AI Tool for Automated Analysis of Large-scale Unstructured Clinical Cine CMR Databases", European Heart Journal Digital Health, 2023. (paper, see also press release)
3 July 2023: New journal paper by Nhat Phung now available online:
P. T. H. Nhat, N. V. Hao, P. V. Tho, H. Kerdegari, L. Pisani, L. N. M. Thu, L. T. Phuong, H. T. H. Duong, D. B. Thuy, A. McBride, M. Xochicale, M. J. Schultz, R. Razavi, A. P. King, L. Thwaites, N. V. V. Chau, S. Yacoub, VITAL Consortium & A. Gomez, "Clinical Benefit of AI-assisted Lung Ultrasound in a Resource-limited Intensive Care Unit", Critical Care, 2023. (paper)
6 June 2023: New journal paper by Tareen Dawood now available online:
T. Dawood, C. Chen, B. S. Sidhu, B. Ruijsink, J. Gould, B. Porter, M. K. Elliot, V. Mehta, C. A. Rinaldi, E. Puyol-Antón, R. Razavi, A. P. King, "Uncertainty Aware Training to Improve Deep Learning Model Calibration for Classification of Cardiac MR Images", Medical Image Analysis, 2023. (paper)
4 May 2023: New conference paper by Shaheim Ogbomo-Harmitt now available online:
S. Ogbomo-Harmitt, J. Grzelak, A. Qureshi, A. P. King, O. Aslanidi, "TESSLA: Two-Stage Ensemble Scar Segmentation for the Left Atrium", Proceedings MICCAI STACOM Challenge on Left Atrial and Scar Quantification and Segmentation, 2023. (paper)
6 February 2023: New conference paper by Tareen Dawood accepted at ISBI 2023:
T. Dawood, E. Chan, R. Razavi, A. P. King, E. Puyol-Antón, "Addressing Deep Learning Model Calibration Using Evidential Neural Networks and Uncertainty-Aware Training", Proceedings ISBI, 2023. (paper)