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, Sébastien Jodogne, 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 UCLouvain 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 foundation 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

As an illustration, get an insight into Prof. Philippe Lefèvre's research which combines space and physical experiences (in French - October 2022) :

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. Schiltz, Félicien; Delhaye, Benoit; Thonnard, Jean-Louis; Lefèvre, Philippe. Grip Force is Adjusted at a Level That Maintains an Upper Bound on Partial Slip Across Friction Conditions During Object Manipulation. In: IEEE Transactions on Haptics, Vol. 15, no.1, p. 2-7 (2022). doi:10.1109/toh.2021.3137969.

2. De Comite, Antoine; Crevecoeur, Frédéric; Lefèvre, Philippe. Reward-Dependent Selection of Feedback Gains Impacts Rapid Motor Decisions. In: eneuro, Vol. 9, no.2, p. ENEURO.0439-21.2022 (2022). doi:10.1523/eneuro.0439-21.2022.

3. Murdison, T. Scott; Standage, Dominic I.; Lefèvre, Philippe; Blohm, Gunnar. Effector-dependent stochastic reference frame transformations alter decision-making. In: Journal of Vision, Vol. 22, no.8, p. 1 (2022). doi:10.1167/jov.22.8.1.

4. De Comite, Antoine; Crevecoeur, Frédéric; Lefèvre, Philippe. Continuous Tracking of Task Parameters Tunes Reaching Control Online. In: eneuro, Vol. 9, no.4, p. ENEURO.0055-22.2022 (2022). doi:10.1523/eneuro.0055-22.2022.

5. Crevecoeur, Frédéric; Mathew, James; Lefèvre, Philippe. Separability of Human Motor Memories during reaching adaptation with force cues. In: PLOS Computational Biology, Vol. 18, no.10, p. e1009966 (2022). doi:10.1371/journal.pcbi.1009966.

6. De Comite, Antoine; Crevecoeur, Frédéric; Lefèvre, Philippe. Reward-Dependent Selection of Feedback Gains Impacts Rapid Motor Decisions. In: eneuro, Vol. 9, no.2, p. ENEURO.0439-21.2022 (2022). doi:10.1523/eneuro.0439-21.2022.

7. Kasuga, Shoko; Crevecoeur, Frédéric; Cross, Kevin P.; Balalaie, Parsa; Scott, Stephen H. Integration of proprioceptive and visual feedback during online control of reaching. In: Journal of Neurophysiology, Vol. 127, no.2, p. 354-372 (2022). doi:10.1152/jn.00639.2020.

8. Delhaye, Benoit; Jarocka, Ewa; Barrea, Alan; Thonnard, Jean-Louis; Edin, Benoni; Lefèvre, Philippe. High-resolution imaging of skin deformation shows that afferents from human fingertips signal slip onset. In: eLife, Vol. 10 (2021). doi:10.7554/elife.64679.

9. Mathew, James; Lefèvre, Philippe; Crevecoeur, Frédéric. Savings in Human Force Field Learning Supported by Feedback Adaptation. In: eneuro, Vol. 8, no.5, p. ENEURO.0088-21.2021 (2021). doi:10.1523/eneuro.0088-21.2021.

10. Mathew, James; Crevecoeur, Frédéric. Adaptive Feedback Control in Human Reaching Adaptation to Force Fields. In: Frontiers in Human Neuroscience, Vol. 15 (2021). doi:10.3389/fnhum.2021.742608.

Conference Papers

1. Gerniers, Alexander; Dupont, Pierre. MicroCellClust 2: a hybrid approach for multivariate rare cell mining in large-scale single-cell data. In: 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022, 978-1-6654-6819-0, p. 148-153 xxx. doi:10.1109/bibm55620.2022.9995176.

2. Dessain, Quentin; Delinte, Nicolas; Macq, Benoît; Rensonnet, Gaëtan. Fast multi-compartment microstructure fingerprinting using deep neural networks. 2022 xxx.

3. Jodogne, Sébastien. Rendering Medical Images using WebAssembly. In: Proc. of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (Volume 2), 2022, 978-989-758-552-4, 43-51 xxx. doi:10.5220/0000156300003123.

4. El Khoury, Karim; Fockedey, Martin; Brion, Eliott; Macq, Benoît. Amélioration de la robustesse de l’U-Net 3D contre la compression JPEG2000 pour la segmentation des organes pelviens masculins.. In: CORESA 2021, 2021 xxx.

5. Kirkove, Delphine; Barthelemy, Nicole; Coucke, Philippe; Mievis, Carole; Ben Mustapha, Selma; Dardenne, Nadia; Jodogne, Sébastien; Pétré, Benoît. Etude pilote : évaluation de l'impact de l'utilisation de l'imagerie médicale comme outil d'éducation thérapeutique du patient en radiothérapie. 2021 xxx.

6. Mathew, James; Lefèvre, Philippe; Crevecoeur, Frédéric. Savings in human reaching is linked to feedback adaptation. 2021 xxx.

7. Crevecoeur, Frédéric; Mathew, James; Lefèvre, Philippe. Force cues flexibly separate motor memories in human reaching adaptation. 2021 xxx.

8. Aspeel, Antoine; Gouverneur, A.; Jungers, Raphaël M.; Macq, Benoît. Optimal Measurement Budget Allocation For Particle Filtering. In: IEEE International Conference on Image Processing (ICIP). Vol. 1, no. 1, p. 1-5 (25-28 October 2020). IEEE, 2020, 978-1-7281-6396-3 xxx. doi:10.1109/ICIP40778.2020.9190702.

9. El Khoury, Ghady; Libouton, Xavier; Thonnard, Jean-Louis; Lefèvre, Philippe; Penta, Massimo; Barbier, Olivier. Manual Ability in Hand Surgery Patients: Validation of the ABILHAND Scale in Four Diagnostic Groups. 2020 xxx.

10. Mathew, James; Bastin, M; Lefèvre, Philippe; Crevecoeur, Frédéric. Correlates of online changes in movement representations in 240ms. 2019 xxx.