DKE research theme

Signals, Complex Systems and Images (SCSI)

Mathematically describing the situations that generate signals, helps to make the most of their data. Research within SCSI focusses on developing new techniques to analyze signals, images and systems, and develops ways to describe (signal-generating) systems mathematically.

Highlighted publications

  • Bennis, F. C., Teeuwen, B., Zeiler, F. A., Elting, J. W., van der Naalt, J., Bonizzi, P., Delhaas, T., & Aries, M. J. (2020). Improving Prediction of Favourable Outcome After 6 Months in Patients with Severe Traumatic Brain Injury Using Physiological Cerebral Parameters in a Multivariable Logistic Regression Model. Neurocritical Care, 33(2), 542-551.
  • Bonizzi, P., Meste, O., Zeemering, S., Karel, J., Lankveld, T., Crijns, H., Schotten, U., & Peeters, R. (2020). A novel framework for noninvasive analysis of short-term atrial activity dynamics during persistent atrial fibrillation. Medical & Biological Engineering & Computing, 58(9), 1933-1945.
  • Bonizzi, P., Peeters, R., Zeemering, S., van Hunnik, A., Meste, O., & Karel, J. (2019). Detection of Spatio-Temporal Recurrent Patterns in Dynamical Systems. Frontiers in Applied Mathematics and Statistics, 5(36), 1-13.
  • Bresolin, D., Collins, P., Geretti, L., Segala, R., Villa, T., & Zivanovic Gonzalez, S. (2020). A computable and compositional semantics for hybrid automata. In HSCC '20: Proceedings of the 23rd International Conference on Hybrid Systems: Computation and Control (pp. 1-11). [18] The Association for Computing Machinery.
  • Clerx, M., Heijman, J., Collins, P., & Volders, P. G. A. (2018). Predicting changes to I-Na from missense mutations in human SCN5A. Scientific Reports, 8(1), [12797].
  • Cluitmans, M., Karel, J., Bonizzi, P., Volders, P., Westra, R., & Peeters, R. (2018). Wavelet-promoted sparsity for non-invasive reconstruction of electrical activity of the heart. Medical & Biological Engineering & Computing, 56(11), 2039-2050.
    Collins, P., & Mitchell, K. (2019). Graph duality in surface dynamics. Journal of Nonlinear Science, 29(5), 2103-2135.
  • Collins, P., van Helvoort, S., Khimshiasvili, G., Marsella, A., Molenaar, J., and Swaenen, L. (2019).  Prediction of print success for concrete 3d printing. In Jaap Molenaar and Hans Stigter, editors, Proceedings of the 148th European Study Group Mathematics with Industry (SWI)
  • Davarzani, N., Sanders-van Wijk, S., Maeder, M. T., Rickenbacher, P., Smirnov, E., Karel, J., Suter, T., de Boer, R. A., Block, D., Rolny, V., Zaugg, C., Pfisterer, M. E., Peeters, R., & Brunner-La Rocca, H. (2018). Novel concept to guide systolic heart failure medication by repeated biomarker testing—results from TIME-CHF in context of predictive, preventive, and personalized medicine. The EPMA Journal, 9(2), 161-173.
  • Ismailoglu, F., Cavill, R., Smirnov, E., Zhou, S., Collins, P., & Peeters, R. (2020). Heterogeneous Domain Adaptation for IHC Classification of Breast Cancer Subtypes. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(1), 347-353.
  • Karel, J., & Peeters, R. (2018). Orthogonal Matched Wavelets with Vanishing Moments: A Sparsity Design Approach. Circuits Systems and Signal Processing, 37(8), 3487-3514.
  • Monnery, B. D., Jerca, V. V., Sedlacek, O., Verbraeken, B., Cavill, R., & Hoogenboom, R. (2018). Defined High Molar Mass Poly(2-Oxazoline)s. Angewandte Chemie-International Edition, 57(47), 15400-15404.
  • O'Donovan, S. D., Driessens, K., Lopatta, D., Wimmenauer, F., Lukas, A., Neeven, J., Smirnov, E., Lenz, M., Ertaylan, G., Jennen, D. G. J., van Riel, N. A. W., Cavill, R., Peeters, R. L. M., & de Kok, T. M. C. M. (2020). Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes. PLOS ONE, 15(8), [e0236392].
  • Salinet, J., Molero, R., Schlindwein , F., Karel, J., Rodrigo, M., Rojo-Álvarez, J. L., Berenfeld, O., Climent, A., Zenger, B., Vanheusden, F., Paredes Jimena, G. S., MacLeod, R., Atienza, F., Guillem, M., Cluitmans, M., & Bonizzi, P. (2021). Electrocardiographic imaging for atrial fibrillation: a perspective from computer models and animal experiments to clinical value. Frontiers in physiology, 12, [653013].
  • Zeemering, S., Lankveld, T. A. R., Bonizzi, P., Limantoro, I., Bekkers, S. C. A. M., Crijns, H. J. G. M., & Schotten, U. (2018). The electrocardiogram as a predictor of successful pharmacological cardioversion and progression of atrial fibrillation. EP Europace, 20(7), E96-E104.
  • Zeemering, S., van Hunnik, A., van Rosmalen, F., Bonizzi, P., Scaf, B., Delhaas, T., Verheule, S., & Schotten, U. (2020). A Novel Tool for the Identification and Characterization of Repetitive Patterns in High-Density Contact Mapping of Atrial Fibrillation. Frontiers in physiology, 11, [570118].

See all DKE publications