Publications

Google Scholar Profile

Book Chapters - White Papers

Peer-Reviewed Articles in Journals

Peer-Reviewed Articles-Abstracts in Conferences-Workshops

  • M. Alkan, G. Veldtman, F. Deligianni, Riemannian Prediction of Anatomical Diagnoses in Congenital Heart Disease based on 12-lead ECG's, IEEE International Symposium on Biomedical Imaging (IEEE ISBI), under review.

  • A. Tragakis, Q. Liu, C. Kaul, S.K. Roy, H. Dai, F. Deligianni, R. Murray-Smith, D. Faccio, GLFNet: Global-Local (Frequency) Filter Networks for efficient Medical Image Segmentation, IEEE International Symposium on Biomedical Imaging (IEEE ISBI), under review.

  • F. Dalla Serra, C. Wang, F. Deligianni, J. Dalton, and A. Q. O'Neil, Controllable Chest X-Ray Report Generation from Longitudinal Representations, Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

  • M. Malek-Podjaski and F. Deligianni, Adversarial Attention for Human Motion Synthesis, IEEE Symposium Series on Computational Intelligence (SSCI), 2023.

  • N. Kaur, F. Deligianni, P. Pellicori, J.G.F. Clelland, Use of machine learning to predict mortality in patients with type 2 diabetes mellitus, according to socioeconomic status, European Heart Journal (abstract), 2023.

  • N. Kaur, P. Pellicori, F. Deligianni, J.G.F. Clelland, Use of machine learning to predict drivers of incident heart failure in patients with type 2 diabetes mellitus, Heart Failure (abstract), 2023.

  • Q. Liu, X. Gu, P. Henderson, F. Deligianni, Multi-Scale Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation, BMVC, 2023.

  • Q. Liu, C. Kaul, J. Wang, C. Anagnostopoulos, R. Murray-Smith, F. Deligianni, Optimizing Vision Transformers for Medical Image Segmentation, IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023.

  • T. Aladwani, C. Anagnostopoulos, K. Kolomvatsos, I. Alghamdi, F. Deligianni, Query-driven Edge Node Selection in Distributed Learning Environments, IEEE International Conference on Data Engineering, 2023.

  • F.D. Serra, W. Clackett, H. MacKinnon, C. Wang, F. Deligianni, J. Dalton, A.Q. O’Neil, Multimodal Generation of Radiology Reports using Knowledge-Grounded Extraction of Entities and Relations, Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022.

  • F.D. Serra, G. Jacenkow, F. Deligianni, J. Dalton, A.Q. O'Neil, Improving Image Representations via MoCo Pre-Training for Multimodal CXR Classification, MIUA, 2022.

  • M. Malek-Podjaski, F. Deligianni, Towards Explainable, Privacy-Preserved Human-Motion Affect Recognition, IEEE Symposium Series on Computational Intelligence, 2021.

  • I. Domingos, G.Z. Yang and F. Deligianni, Intention Detection of Gait Adaptation in Natural Settings’, IEEE Symposium Series on Computational Intelligence, 2021. (Best Runner Up Award - IEEE Brain)

  • Y. Jones, F. Deligianni and J Dalton, Improving ECG Classification Interpretability Using Saliency Maps, IEEE BIBE, 2020. (Best paper award)

  • F. Deligianni, J. Clayden and G-Z. Yang, Comparison of Brain Networks based on Predictive Models of Connectivity, IEEE BIBE, 2019. (Best paper award)

  • D. Freer, F. Deligianni and G.Z. Yang, Adaptive Riemannian BCI for Enhanced Motor Imagery Training Protocols, IEEE BSN, 2019. (ORAL PRESENTATION)

  • F. Deligianni, H. Singh, H. Modi, A. Darzi, D.R. Leff, G.Z Yang, Expertise Related Disparity in Prefrontal-Motor Brain Connectivity, HSMR, 2018. (ORAL PRESENTATION) pdf

  • I. Domingos, F. Deligianni, G.Z. Yang, Dry versus Wet EEG electrode systems in Motor Imagery Classification, The UK-RAS Network Conference on Robotics and Autonomous Systems, Bristol, 2018

  • D.D. Zhang, J.Q. Zheng, J. Fathi, M. Sun, F. Deligianni, G.Z Yang, Motor Imagery Classification based on RNNs with Spatiotemporal-Energy Feature Extraction, The UK-RAS Network Conference on Robotics and Autonomous Systems, Bristol, 2018.

  • X. Gu, F. Deligianni, B. Lo, W. Chen, G.Z. Yang, Markerless gait analysis based on a single RGB camera, IEEE BSN, 42-45, 2018. pdf

  • F. Deligianni, D.W. Carmichael, C.A. Clark and J.D. Clayden, NODDI and Tensor-based Microstructural Indices as Predictors of Functional Connectivity, ISMRM British Chapter, 2015. (ORAL PRESENTATION)

  • F. Deligianni, D.W. Carmichael, C.A. Clark and J.D. Clayden, A prediction framework of functional from structural connectomes reveals relationships between NODDI and tensor-based micro-structural indices, Symposium on Big Data Initiatives for Connectomics Research, International conference on Brain Informatics and Health, 2015. (ORAL PRESENTATION)

  • F. Deligianni, C.A. Clark and J.D. Clayden, Prediction of functional from structural connectomes across micro-structural indices, ISMRM British Chapter, 2014. (ORAL PRESENTATION)

  • F. Deligianni, M. Centeno, D.W. Carmichael and J.D. Clayden, Relating resting-state fMRI and EEG brain connectivity across frequency bands, ISMRM, 2014. (ORAL PRESENTATION) (OHBM14 pdf)

  • F. Deligianni, C.A. Clark and J.D. Clayden, Evaluating structural brain networks based on their performance in predicting functional connectivity, ISMRM, 2014.

  • C.S. Parker, F. Deligianni, M.J. Cardoso, P. Daga, M. Modat, C.A. Clark, S. Ourselin, J.D. Clayden, Consensus between pipelines in whole brain structural connectivity networks, ISMRM, 2014. (ORAL PRESENTATION)

  • F. Deligianni, C.A. Clark, and J.D. Clayden, A Framework to Compare Tractography Algorithms Based on their Performance in Predicting Functional Networks, MICCAI-MBIA, 2013. (ORAL PRESENTATION) pdf

  • F. Deligianni, M. Centeno, D.W. Carmichael and J.D. Clayden, Quantitative Agreement between fMRI and EEG Brain Connectivity Matrices in Different Frequency Bands, BaCI, 2013.

  • F. Deligianni, G. Varoquaux, B. Thirion, E. Robinson, D.J. Sharp, A. D. Edwards and D. Rueckert, Relating brain functional connectivity to anatomical connections: Model Selection, NIPS-MLNI, 2011. (ORAL PRESENTATION) pdf

  • F. Deligianni, G. Varoquaux, B. Thirion, E.Robinson, D.Sharp, A.Edwards, and D.Rueckert, A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections, IPMI, 296-307, 2011. pdf

  • F. Deligianni, E. C. Robinson, D. Sharp, A. D. Edwards, D. Rueckert, and D. C. Alexander, Exploiting Hierarchy in Structural Brain Networks, ISBI, 871-874, 2011. (ORAL PRESENTATION) pdf

  • F. Deligianni, E. C. Robinson, C. F. Beckmann, D. Sharp, A. D. Edwards, and D. Rueckert, Inference of Functional Connectivity from Direct and Indirect Structural Brain Connections, ISBI, 849-852, 2011. pdf

  • F. Deligianni, E. C. Robinson, C. F. Beckmann, D. Sharp, A. D. Edwards, and D. Rueckert, Inference of Functional Connectivity from Structural Brain Connectivity, ISBI, 1113-1116, 2010. pdf

  • E. C. Robinson, F. Deligianni, A. Hammers, D. Rueckert and A. D. Edwards, A Probabilistic White Matter Atlas Approach to Assessing Age Related Changes in the Brain, ISMRM, 2010.

  • A. Senju, F. Deligianni, G. Gergely, and G. Csibra, Gaze Following Depends on a Preceding Ostensive Signal in Early Infancy, Workshop on Pragmatic Development, Lyon, France, 2009.

  • F. Deligianni, A. Chung, and G.-Z. Yang, Non-Rigid 2D-3D Registration with Catheter Tip EM Tracking for Patient Specific Bronchoscope Simulation, MICCAI, 281-288, 2006. (ORAL PRESENTATION) pdf

  • B. Lo, F. Deligianni, and G.-Z. Yang, Source Recovery for Body Sensor Network, BSN, 199-202, 2006.

  • D. Leff, H. Peck, R. Aggarwal, F. Deligianni, C. Elwell, D. Delpy, G. Yang, and A. Darzi, Optical Mapping of the Frontal Cortex During Learning of a Surgical Knot-Tying Task, a Pilot Study, HBM, 140-147, 2006.

  • D. Leff, P. Koh, R. Aggarwal, J. Leong, F. Deligianni, C. Elwell, D. Delpy, A. Darzi, G. Yang, Optical Mapping of the Frontal Cortex During a Surgical Knot-Tying Task, Feasibility Study, MICCAI, 140-7, 2006.

  • F. Deligianni, A. Chung, and G. Z. Yang, Predictive Camera Tracking for Bronchoscope Simulation with Condensation, MICCAI, 910-916, 2005. pdf

  • D. Stoyanov, G. P. Mylonas, F. Deligianni, A. Darzi, and G. Z. Yang, Soft-Tissue Motion Tracking and Structure Estimation for Robotic Assisted Mis Procedures, MICCAI, 139-146, 2005.

  • G. P. Mylonas, D. Stoyanov, F. Deligianni, A. Darzi, and G. Z. Yang, Gaze-Contingent Soft Tissue Deformation Tracking for Minimally Invasive Robotic Surgery, MICCAI, 843-850, 2005.

  • A. Chung, F. Deligianni, M. Elhelw, P. Shah, A. Wells, and G. Z. Yang, Assessing Realism of Virtual Bronchoscopy Images Via Specialist Survey and Eye-Tracking, MIPS XI, 2005.

  • A. J. Chung, F. Deligianni, P. Shah, A. Wells, and G. Z. Yang, Video Driven Finite Element Deformation Models for Surgical Simulation, Communication, MICCAI, 2005.

  • F. Deligianni, A. Chung, and G. Z. Yang, Decoupling of Respiratory Motion with Wavelet and Principal Component Analysis, MIUA, 13-16, 2004. (ORAL PRESENTATION) pdf

  • A. J. Chung, P. J. Edwards, F. Deligianni, and G. Z. Yang, Freehand Cocalibration of an Optical and Electromagnetic Tracker for Navigated Bronchoscopy, MIAR, 320-328, 2004.

  • A. J. Chung, F. Deligianni, P. Shah, A. Wells, and G. Z. Yang, Enhancement of Visual Realism with BRDF for Patient Specific Bronchoscopy Simulation, MICCAI, 486-493, 2004.

  • A. J. Chung, F. Deligianni, X.-P. Hu, and G. Z. Yang, Visual Feature Extraction Via Eye Tracking for Saliency Driven 2D-3D Registration, ETRA, 49-54, 2004.

  • F. Deligianni, A. Chung, and G. Z. Yang, pq-Space Based 2D-3D Registration for Endoscope Tracking, 'MICCAI’, 311-318, 2003. (ORAL PRESENTATION) pdf

  • J. X. Gao, S. Masood, F. Deligianni, and G. Z. Yang, Reconstruction of 3D Deformation from 2D MR Velocity Mapping with Incompressibility Constraints, IEEE EMBS, 134-137, 2003.

Others

Online Available Datasets

Graduate Research

Invited talks

Media Attention

Other Awards and Activities

  • EPSRC New Investigator Award, 2022-2025.

  • Semi-flex Grant, Royal Society, 2022-2023.

  • EPSRC Network grant: Human Motion Analysis - Agency, Negotiation and Legibility in Data Handling, 2020-2021.

  • Best Runner Up Award - IEEE Brain (IEEE Symposium Series on Computational Intelligence), 2021.

  • Best Paper Award in Bioengineering (IEEE 20th International Conference on Bioinformatics and Bioengineering), 2020.

  • Best Paper Award (IEEE 19th International Conference on Bioinformatics and Bioengineering), 2019.

  • MRC Training Fellow, 2008 - 2011.