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. Chiêm, Benjamin; Abbas, Kausar; Amico, Enrico; Duong-Tran, Duy; Crevecoeur, Frédéric; Goni, Joaquin. Improving Functional Connectome Fingerprinting with Degree-Normalization. In: Brain Connectivity, (2021). doi:10.1089/brain.2020.0968 (Accepté/Sous presse). http://hdl.handle.net/2078.1/246557

2. Moreau, Grégoire; François-Lavet, Vincent; Desbordes, Paul; Macq, Benoît. Reinforcement Learning for Radiotherapy Dose Fractioning Automation. In: Biomedicines, Vol. 9, no.2, p. 214 (2021). doi:10.3390/biomedicines9020214. http://hdl.handle.net/2078.1/245680

3. El Khoury, Karim; Fockedey, Martin; Brion, Eliott; Macq, Benoît. Improved 3D U-Net robustness against JPEG 2000 compression for male pelvic organ segmentation in radiotherapy. In: Journal of Medical Imaging, Vol. 8, no.4 (2021). doi:10.1117/1.JMI.8.4.041207. http://hdl.handle.net/2078.1/245039

4. Gerniers, Alexander; Bricard, Orian; Dupont, Pierre. MicroCellClust: mining rare and highly specific subpopulations from single-cell expression data. In: Bioinformatics, Vol. -, no.btab239, p. 1-7 (2021). doi:10.1093/bioinformatics/btab239. http://hdl.handle.net/2078.1/245010

5. Chiêm, Benjamin; Crevecoeur, Frédéric; Delvenne, Jean-Charles. Structure-informed functional connectivity driven by identifiable and state-specific control regions. In: Network Neuroscience, , p. 1-37 (2021). doi:10.1162/netn_a_00192 (Accepté/Sous presse). http://hdl.handle.net/2078.1/244602

6. Danion, Frederic R.; Mathew, James; Gouirand, Niels; Brenner, Eli. More precise tracking of horizontal than vertical target motion with both the eyes and hand. In: Cortex, Vol. 134, p. 30-42 (2021). doi:10.1016/j.cortex.2020.10.001. http://hdl.handle.net/2078.1/241401

7. Nian, Rui; Gao, Mingshan; Kong, Shuang; Yu, Junjie; Wang, Ruirui; Li, Xueshan; Zhang, Shichang; Hao, Baochen; Xu, Xiao; Che, Renzheng; Ai, Qinghui; Macq, Benoît. Online fat detection and evaluation in modelling digital physiological fish. In: Aquaculture Research, Vol. 51, no.8, p. 3175-3190 (2020). http://hdl.handle.net/2078.1/245832

8. Rensonnet, Gaëtan; Rafael-Patiño, Jonathan; Macq, Benoît; Thiran, Jean-Philippe; Girard, Gabriel; Pizzolato, Marco. A Signal Peak Separation Index for axisymmetric B-tensor encoding. In: Medical Physics Series, (2020). http://hdl.handle.net/2078.1/245686

9. Desbordes, Paul; Diksha, undefined; Macq, Benoît. Prognostic Power of Texture Based Morphological Operations in a Radiomics Study for Lung Cancer. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Proceedings, (2021). http://hdl.handle.net/2078.1/245684

10. Coutinho, Jonathan D; Lefèvre, Philippe; Blohm, Gunnar. Confidence in predicted position error explains saccadic decisions during pursuit. In: Journal of Neurophysiology, (2020). doi:10.1152/jn.00492.2019. http://hdl.handle.net/2078.1/242217


Conference Papers


1. Mathew, James; Lefèvre, Philippe; Crevecoeur, Frédéric. Savings in human reaching is linked to feedback adaptation. 2021 xxx. http://hdl.handle.net/2078.1/246405

2. Crevecoeur, Frédéric; Mathew, James; Lefèvre, Philippe. Force cues flexibly separate motor memories in human reaching adaptation. 2021 xxx. http://hdl.handle.net/2078.1/242195

3. Aspeel, Antoine; Gouverneur, A.; Jungers, Raphaël M.; Macq, Benoît. Optimal Measurement Budget Allocation For Particle Filtering. IEEE, 2020, 978-1-7281-6396-3 xxx. doi:10.1109/ICIP40778.2020.9190702. http://hdl.handle.net/2078.1/238953

4. Mathew, James; Bastin, M; Lefèvre, Philippe; Crevecoeur, Frédéric. Correlates of online changes in movement representations in 240ms. 2019 xxx. http://hdl.handle.net/2078.1/241745

5. Danion, Frederic R; Mathew, James; Gouirand, Niels; Brenner, Eli. Separate contribution of eye movements to hand tracking and its adaptation to visuomotor rotation. 2019 xxx. http://hdl.handle.net/2078.1/241744

6. Lefèvre, Philippe; Mathew, James; Crevecoeur, Frédéric. Online changes in movement representations could be preserved in memory for at least 500ms. 2019 xxx. http://hdl.handle.net/2078.1/241743

7. Mathew, James; De Rugy, Aymar; Danion, Frederic R. Hand coordination in space overrules the optimization of variability and effort during bimanual tracking. 2019 xxx. http://hdl.handle.net/2078.1/241742

8. Crevecoeur, Frédéric; Mathew, James; Lefèvre, Philippe. Learning adapted feedback responses to unpredictable force fields during reaching. 2019 xxx. http://hdl.handle.net/2078.1/241740

9. Mathew, James; Lefèvre, Philippe; Crevecoeur, Frédéric. Correlates of online changes in movement representations in 250ms. 2019 xxx. http://hdl.handle.net/2078.1/241048

10. Crevecoeur, Frédéric; Lefèvre, Philippe; Mathew, James. Learning compensation for different force fields and perturbation directions randomly applied during reaching. 2019 xxx. http://hdl.handle.net/2078.1/241041