Biomedical Engineering

Several research groups carry out research in the field of biomedical engineering. It involves the following activities summarized in more details below: Bioinformatics and computational biology, Biomedical data analysis, Biosensors, Medical Imaging, Modelling of biological and physiological systems.

Principal Investigators :

Pierre-Antoine Absil, Frédéric Crevecoeur, Pierre Dupont, Denis Flandre, Laurent Jacques, Philippe Lefèvre, Benoit Macq, Michel Verleysen

Research Labs :

Machine Learning Group, INMA (Mathematical Engineering research division), Image and Signal Processing Group (ISPGroup)

Research Areas :

ICTEAM is involved in Transcriptomics and High-Throughput Technologies. This research activity focuses on the identification of biomarkers from gene expression data, as measured by high-throughput technologies such as high-density DNA microarrays or next generation sequencing platforms. These biomarkers may be used for medical diagnosis, prognosis or prediction of the response to a treatment. Our research objectives also include the link between transcriptomic data and functional analysis from a system biology viewpoint. Several collaborations exist on those topics with the UCL Institute for Experimental and Clinical Research in the context of cancer research, allergy prediction among newborns and early diagnosis of arthritis.

Current projects also involve analysis and filtering of biomedical data and signals. It concerns a wide variety of applications based on the expert knowledge on data analysis and processing to the biomedical field:

  • analysis of biomedical signals (including ECG, EEG, etc.) for automatic pre-diagnosis
  • filtering of medical scan images for contour extraction

Several research projects aim at developing biosensors and biomedical applications of electronics:

  • application to monitoring of respiration (micro-systems)
  • low power systems for biomedical applications
  • security and cryptography for biomedical applications

ICTEAM pursues research on image processing tools and applications for the use in various medical contexts (radiotherapy, proton therapy, brachytherapy, surgery) and at different stages of treatment (planning, execution and follow-up). The research focuses on:

  • rigid and non-rigid image registrations methods for 2D-3D and 3D-3D images both for single and multiple modalities as well as for surfaces;
  • segmentation techniques either using prior knowledge (atlas-based) or allowing user interaction (graph cuts)
  • human-computer interactions to create intuitive user interfaces for the clinical world.

Another field of research is the solving of inverse problems from generalized sparsity prior (with applications in optics and X-ray CT), Compressed Sensing (theory and application), theoretical questions linked to the design of new sensors (for computer vision), applied mathematics for astronomical and biomedical signal processing questions, and representation of data on strange spaces (e.g., sphere, manifolds, or graphs). Besides, research is pursued on EEG reconstruction, transcranial magnetic stimulation, as well as on the use of functional imaging for measuring motion disorders.

The institute is also involved in shape analysis for protein docking. This includes 3D mesh processing and the analysis of protein surface properties.

ICTEAM also has research activities investigating the neural control movement. These activities are based on experimental, clinical and modelling approaches. Among the ongoing projects:

  • interaction between vision and the neural control of movement
  • experimental and modelling study of eye and head movements as well as eye-hand coordination
  • clinical studies: the influence of Duane Retraction Syndrome and Cerebral Palsy on vision and eye movements (St Luc Hospital and fondation JED).
  • dextrous manipulation in micro- and hyper-gravity (supported by Prodex and ESA)
  • the role of internal models: prediction and anticipation in smooth pursuit and saccade programming

Most recent publications

Below are listed the 10 most recent journal articles and conference papers produced in this research area. You also can access all publications by following this link : see all biomedical engineering publications


Journal Articles


1. Kirkove, D; Ben Mustapha, S; Jodogne, Sébastien; Pétré, B. L'utilisation de l'imagerie médicale en tant qu'outil d'éducation thérapeutique du patient en radiothérapie : étude de faisabilité. In: Revue médicale de Liège, Vol. 79, no.S1, p. 100-106 (2024). http://hdl.handle.net/2078.1/287399

2. Jodogne, Sébastien. Apport du logiciel libre en imagerie médicale. In: Revue médicale de Liège, Vol. 79, no.S1, p. 75-83 (2024). http://hdl.handle.net/2078.1/287398

3. Vanbrabant, Martin; Raskin, Jean-Pierre; Flandre, Denis; Kilchytska, Valeriya. Impact of thermal coupling effects on the digital and analog figures of merit of UTBB SOI MOSFET pairs. In: Solid - State Circuits, Vol. 2023, p. 108623 (2023). doi:10.1016/j.sse.2023.108623. http://hdl.handle.net/2078.1/283154

4. Wuyckens, Sophie; Dasnoy-Sumell, Damien; Janssens, Guillaume; Hamaide, Valentin; Huet, Margerie; Loyen, Estelle; Macq, Benoît; Rotsart de Hertaing, Gauthier. OpenTPS -- Open-source treatment planning system for research in proton therapy. In: Medical Physics, (2023). doi:10.48550/arXiv.2303.00365. http://hdl.handle.net/2078.1/283087

5. Loyen, Estelle; Dasnoy-Sumell, Damien; Macq, Benoît. Patient-specific three-dimensional image reconstruction from a single X-ray projection using a convolutional neural network for on-line radiotherapy applications. In: Physics and Imaging in Radiation Oncology, Vol. 26, p. 100444 (2023). doi:10.1016/j.phro.2023.100444. http://hdl.handle.net/2078.1/283085

6. Kalidindi, Hari Teja; Crevecoeur, Frédéric. Human reaching control in dynamic environments. In: Current Opinion in Neurobiology, Vol. 83, p. 102810 (2023). doi:10.1016/j.conb.2023.102810. http://hdl.handle.net/2078.1/280506

7. Córdova Bulens, David; du Bois de Dunilac, Sophie; Delhaye, Benoit; Lefèvre, Philippe; Redmond, Stephen J. Open-source instrumented object to study dexterous object manipulation. In: eNeuro, (2023). doi:10.1101/2023.10.20.563288 (Accepté/Sous presse). http://hdl.handle.net/2078.1/279788

8. Hoffmann, Anne; Crevecoeur, Frédéric. Task Instructions and the Need for Feedback Correction Influence the Contribution of Visual Errors to Reach Adaptation. In: eneuro, Vol. 10, no.9, p. ENEURO.0068-23.2023 (2023). doi:10.1523/eneuro.0068-23.2023. http://hdl.handle.net/2078.1/278768

9. Blondiaux, Florence; Lebrun, Louisien; Hanseeuw, Bernard; Crevecoeur, Frédéric. Impairments of saccadic and reaching adaptation in Essential Tremor are linked to movement execution. In: Journal of Neurophysiology, (2023). doi:10.1152/jn.00165.2023. http://hdl.handle.net/2078.1/278767

10. De Comite, Antoine; Lefèvre, Philippe; Crevecoeur, Frédéric. Continuous evaluation of cost-to-go for flexible reaching control and online decisions. In: PLoS Computational Biology, Vol. 19, no. 9, p. e1011493 (2023). doi:10.1371/journal.pcbi.1011493. http://hdl.handle.net/2078.1/278222


Conference Papers


1. Sadre, Wei; Huet-Dastarac, Margerie; Deffet, Sylvain; Sterpin, Edmond; Barragan Montero, Ana Maria; Jodogne, Sébastien; Lee, John Aldo. PARROT - A Versatile Platform for AI-Driven Image Segmentation and Dose Prediction. In: Proc. of the 5th International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024). 2024 xxx. http://hdl.handle.net/2078.1/291340

2. Langlois, Quentin; Jodogne, Sébastien. Embeddings for Motor Imagery Classification. In: Proc. of IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP 2024). p. 1-6. IEEE, 2024 xxx. doi:10.1109/MLSP58920.2024.10734730. http://hdl.handle.net/2078.1/291339

3. Chatzopoulos, Edouard; Jodogne, Sébastien. Assessing the Impact of Deep Learning Backbones for Mass Detection in Breast Imaging. In: Lecture Notes in Computer Science. Vol. 14976, p. 33-47 (2024). Springer Nature Switzerland: Cham, Switzerland, 2024 xxx. doi:10.1007/978-3-031-67285-9_3. http://hdl.handle.net/2078.1/289661

4. Chatzopoulos, Edouard; Jodogne, Sébastien. Integrated and Interoperable Platform for Detecting Masses on Mammograms. In: Studies in Health Technology and Informatics. Vol. 316, p. 1103-1107 (2024). IOS Press, 2024 xxx. doi:10.3233/SHTI240603. http://hdl.handle.net/2078.1/289660

5. Jodogne, Sébastien. Plateforme libre, intégrée et interopérable pour la détection de masses en mammographie. 2024 xxx. http://hdl.handle.net/2078.1/289658

6. Dessain, Quentin; Simon, Mathieu; Dricot, Laurence; Macq, Benoît. Advanced Motion Correction in Diffusion MRI Acquisition with Gradient Cycling. 2024 xxx. http://hdl.handle.net/2078.1/287540

7. Rotsart de Hertaing, Gauthier; Manjah, Dani; Macq, Benoît. TrajViViT: A Trajectory Video Vision Transformer Network for Trajectory Forecasting. In: Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 2024, 978-989-758-684-2 xxx. doi:10.5220/0012372000003654. http://hdl.handle.net/2078.1/285748

8. Manjah, Dani; Galland, Stéphane; De Vleeschouwer, Christophe; Macq, Benoît. Autonomous Methods in Multisensor Architecture for Smart Surveillance. In: Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, 2024, 978-989-758-680-4 xxx. doi:10.5220/0012395700003636. http://hdl.handle.net/2078.1/285747

9. Pierard, Sébastien; Cioppa, Anthony; Halin, Anaïs; Vandeghen, Renaud; Zanella, Maxime; Macq, Benoît. Pushing AI out of the lab with on-the-fly mixture domain adaptation. 2023 xxx. http://hdl.handle.net/2078.1/283086

10. Huet Dastarac, M.; Zhao, W.; Deffet, S.; Macq, Benoît. PO-1079 PARROT: An end-to-end open source workflow of AI-assisted treatment planning and decision support. In: Radiotherapy & Oncology. Vol. 182, p. S863-S864 (2023). Elsevier Ireland Ltd: Shannon, 2023 xxx. http://hdl.handle.net/2078.1/283084