University of Twente
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prof.dr.ir. R.N.J. Veldhuis (Raymond)

Hoogleraar

Expertises

Engineering & Materials Science
# Biometrics
# Classifiers
# Deep Learning
# Face Recognition
# Feature Extraction
# Image Resolution
# Palmprint Recognition
Medicine & Life Sciences
# Deep Learning

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Publicaties

Recent
van den Oever, L. B., Spoor, D. S., Crijns, A. P. G., Vliegenthart, R., Oudkerk, M. , Veldhuis, R. N. J., de Bock, G. H., & van Ooijen, P. M. A. (2022). Automatic Cardiac Structure Contouring for Small Datasets with Cascaded Deep Learning Models. Journal of medical systems, 46(5), [22]. https://doi.org/10.1007/s10916-022-01810-6
Busch, C., Czajka, A., Deravi, F., Drozdowski, P., Gomez-Barrero, M., Hasse, G., Henniger, O., Kindt, E., Kolberg, J., Nouak, A., Raja, K., Ramachandra, R., Rathgeb, C., Salomon, J. , & Veldhuis, R. (2022). A response to the European Data Protection Supervisor ‘Misunderstandings in Biometrics’ by the European Association for Biometrics. IET biometrics, 11(1), 79-86. https://doi.org/10.1049/bme2.12057
Nagaraj, Y., de Jonge, G., Andreychenko, A., Presti, G., Fink, M. A., Pavlov, N., Quattrocchi, C. C., Morozov, S. , Veldhuis, R., Oudkerk, M., & van Ooijen, P. M. A. (2022). Facilitating standardized COVID-19 suspicion prediction based on computed tomography radiomics in a multi-demographic setting. European radiology. https://doi.org/10.1007/s00330-022-08730-6
Nagaraj, Y., Wisselink, H. J., Rook, M., Cai, J. , Nagaraj, S. B., Sidorenkov, G. , Veldhuis, R., Oudkerk, M., Vliegenthart, R., & van Ooijen, P. (2022). AI-Driven Model for Automatic Emphysema Detection in Low-Dose Computed Tomography Using Disease-Specific Augmentation. Journal of Digital Imaging. https://doi.org/10.1007/s10278-022-00599-7
Spreeuwers, L., Schils, M. , Veldhuis, R. , & Kelly, U. (2022). Practical Evaluation of Face Morphing Attack Detection Methods. In C. Rathgeb, R. Tolosana, R. Vera-Rodriguez, & C. Busch (Eds.), Handbook of Digital Face Manipulation and Detection: From DeepFakes to Morphing Attacks (pp. 351-365). (Advances in Computer Vision and Pattern Recognition). Springer Science + Business Media. https://doi.org/10.1007/978-3-030-87664-7_16
van den Oever, L. B., van Veldhuizen, W. A. , Cornelissen, L. J., Spoor, D. S., Willems, T. P., Kramer, G., Stigter, T., Rook, M., Crijns, A. P. G., Oudkerk, M. , Veldhuis, R. N. J., de Bock, G. H., & van Ooijen, P. M. A. (2022). Qualitative Evaluation of Common Quantitative Metrics for Clinical Acceptance of Automatic Segmentation: a Case Study on Heart Contouring from CT Images by Deep Learning Algorithms. Journal of Digital Imaging, 35(2), 240-247. https://doi.org/10.1007/s10278-021-00573-9
Cui, X., Zheng, S., Heuvelmans, M. A., Du, Y., Sidorenkov, G., Fan, S., Li, Y., Xie, Y., Zhu, Z., Dorrius, M. D., Zhao, Y. , Veldhuis, R. N. J., de Bock, G. H., Oudkerk, M., van Ooijen, P. M. A., Vliegenthart, R., & Ye, Z. (2022). Performance of a deep learning-based lung nodule detection system as an alternative reader in a Chinese lung cancer screening program. European journal of radiology, 146, [110068]. https://doi.org/10.1016/j.ejrad.2021.110068

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Contactgegevens

+31614346251  (mobiel)
+31534893776  (bij geen gehoor)
 
 

Bezoekadres

Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (gebouwnr. 11), kamer 4074
Hallenweg 19
7522NH  Enschede

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Postadres

Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling  4074
Postbus 217
7500 AE Enschede

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Universiteit Twente Drienerlolaan 5
7522 NB Enschede
+31 (0)53 489 9111
info@utwente.nl
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