Publications chair mathematics of imaging & AI (MIA)
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2025
Article
Atypical plume-like events contribute to glutamate accumulation in metabolic stress conditions (2025)iScience, 28(4). Article 112256. Ziebarth, T., Pape, N., Nelson, J. S. E., van Alphen, F. I. M., Kalia, M., Meijer, H. G. E., Rose, C. R. & Reiner, A.https://doi.org/10.1016/j.isci.2025.112256Optimal Transport on the Lie Group of Roto-translations (2025)SIAM journal on imaging sciences, 18(2), 789-821 (E-pub ahead of print/First online). Bon, D., Pai, G., Bellaard, G., Mula, O. & Duits, R.https://doi.org/10.1137/24M1641531SIRE: Scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks (2025)Medical image analysis, 101. Article 103467. Alblas, D., Suk, J., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.1016/j.media.2025.103467Feasibility of tomographic freehand three-dimensional ultrasound for surveillance of abdominal aortic aneurysms after endovascular repair (2025)Vascular (E-pub ahead of print/First online). van Rijswijk, R. E., Everink, S. R. T., Wolterink, J. M., Reijnen, M. M. P. J. & Groot Jebbink, E.https://doi.org/10.1177/17085381251327171Deep learning-based pelvimetry in pelvic MRI volumes for pre-operative difficulty assessment of total mesorectal excision (2025)Surgical endoscopy, 39(3), 1536-1543. Baltus, S. C., Geitenbeek, R. T. J., Frieben, M., Thibeau-Sutre, E., Wolterink, J. M., Tan, C. O., Vermeulen, M. C., Consten, E. C. J. & Broeders, I. A. M. J.https://doi.org/10.1007/s00464-024-11485-4Periodic Center Manifolds for DDEs in the Light of Suns and Stars (2025)Journal of dynamics and differential equations, 37, 815–858. Lentjes, B., Spek, L., Bosschaert, M. M. & Kuznetsov, Y. A.https://doi.org/10.1007/s10884-023-10289-9Widespread neuronal chaos induced by slow oscillating currents (2025)Chaos, 35(3). Article 033120. Scully, J., Hinsley, C., Bloom, D., Meijer, H. G. E. & Shilnikov, A. L.https://doi.org/10.1063/5.0248001Developing Trustworthy Artificial Intelligence Models to Predict Vascular Disease Progression: the VASCUL-AID-RETRO Study Protocol (2025)Journal of Endovascular Therapy (E-pub ahead of print/First online). Rijken, L., Zwetsloot, S., Smorenburg, S., Wolterink, J., Išgum, I., Marquering, H., van Duivenvoorde, J., Ploem, C., Jessen, R., Catarinella, F., Lee, R., Bera, K., Buisan, J., Zhang, P., Dias-Neto, M., Raffort, J., Lareyre, F., Muller, C., Koncar, I., … Yeung, K. K.https://doi.org/10.1177/15266028251313963A sparse optimization approach to infinite infimal convolution regularization (2025)Numerische Mathematik, 157(1), 41-96. Bredies, K., Carioni, M., Holler, M., Korolev, Y. & Schönlieb, C. B.https://doi.org/10.1007/s00211-024-01439-2Extremal Points and Sparse Optimization for Generalized Kantorovich–Rubinstein Norms (2025)Foundations of Computational Mathematics, 25(1), 103-144. Carioni, M., Iglesias, J. A. & Walter, D.https://doi.org/10.1007/s10208-023-09634-7Multimodal Artificial Intelligence Model for Prediction of Abdominal Aortic Aneurysm Shrinkage After Endovascular Repair ( the ART in EVAR study) (2025)Journal of Endovascular Therapy (E-pub ahead of print/First online). van Rijswijk, R. E., Bogdanovic, M., Roy, J., Yeung, K. K., Zeebregts, C. J., Geelkerken, R. H., Jebbink, E. G., Wolterink, J. M. & Reijnen, M. M. P. J.https://doi.org/10.1177/15266028251314359Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging (2025)IEEE transactions on ultrasonics, ferroelectrics and frequency control (E-pub ahead of print/First online). Zorgdrager, R., Blanken, N., Wolterink, J. M., Versluis, M. & Lajoinie, G.https://doi.org/10.1109/TUFFC.2025.3537298Deep learning for segmentation of colorectal carcinomas on endoscopic ultrasound (2025)Techniques in coloproctology, 29(1). Article 20. Noort, F. v. d., ter Borg, F., Guitink, A., Faber, J. & Wolterink, J. M.https://doi.org/10.1007/s10151-024-03056-5NeRF-OR: neural radiance fields for operating room scene reconstruction from sparse-view RGB-D videos (2025)International journal of computer assisted radiology and surgery, 20, 147-156. Gerats, B. G. A., Wolterink, J. M. & Broeders, I. A. M. J.https://doi.org/10.1007/s11548-024-03261-5Quantitative aortic Na[18F]F positron emission tomography computed tomography as a tool to associate vascular calcification with major adverse cardiovascular events (2025)European journal of nuclear medicine and molecular imaging, 52, 501-509. Lieverse, T. G. F., van Praagh, G. D., Mulder, D. J., Lambers Heerspink, H. J., Wolterink, J. M. & Slart, R. H. J. A.https://doi.org/10.1007/s00259-024-06901-9
Conference contribution
Preface (2025)In 9th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2024, held in conjunction with the 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024 (pp. v) (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Fernandez, V., Wolterink, J. M., Wiesner, D., Remedios, S., Zuo, L. & Casamitjana, A.
Dataset
One cut conditional gradient method for total variation regularization (2025)[Dataset Types › Dataset]. Zenodo. Cristinelli, G., Iglesias, J. A. & Walter, D.https://doi.org/10.5281/zenodo.15231158Thyroid meshes and presampled SDF values accompanying the paper "Steerable Anatomical Shape Synthesis with Implicit Neural Representations" (2025)[Dataset Types › Dataset]. Zenodo. de Wilde, B., Rietberg, M., Lajoinie, G. & Wolterink, J.https://doi.org/10.5281/zenodo.15100851
Preprint
Perturbation-Aware Distributionally Robust Optimization for Inverse Problems (2025)[Working paper › Preprint]. ArXiv.org (Submitted). van Maarschalkerwaart, F., Mukherjee, S., Sabaté Landman, M., Brune, C. & Carioni, M.https://doi.org/10.48550/arXiv.2503.04646Monotonicity of the jump set and jump amplitudes in one-dimensional TV denoising (2025)[Working paper › Preprint]. ArXiv.org. Cristoferi, R., Ferreira, R., Fonseca, I. & Iglesias, J. A.https://doi.org/10.48550/arXiv.2502.11714Nonlocal perimeters and variations: Extremality and decomposability for finite and infinite horizons (2025)[Working paper › Preprint]. ArXiv.org. Carioni, M., Grande, L. D., Iglesias, J. A. & Schönberger, H.https://doi.org/10.48550/arXiv.2502.05149PDE-DKL: PDE-constrained deep kernel learning in high dimensionality (2025)[Working paper › Preprint]. ArXiv.org. Yan, W., Brune, C. & Guo, M.https://doi.org/10.48550/arXiv.2501.18258Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models (2025)[Working paper › Preprint]. ArXiv.org. Nannini, G., Suk, J., Rygiel, P., Saitta, S., Mariani, L., Maragna, R., Baggiano, A., Pontone, G., Wolterink, J. M. & Redaelli, A.https://doi.org/10.48550/arXiv.2501.09046HypeRL: Parameter-Informed Reinforcement Learning for Parametric PDEs (2025)[Working paper › Preprint]. ArXiv.org. Botteghi, N., Fresca, S., Guo, M. & Manzoni, A.https://doi.org/10.48550/arXiv.2501.04538Deep Networks are Reproducing Kernel Chains (2025)[Working paper › Preprint]. ArXiv.org. Heeringa, T. J., Spek, L. & Brune, C.https://doi.org/10.48550/arXiv.2501.03697
2024
Article
Deep-learning-based extraction of circle of Willis topology with anatomical priors (2024)Scientific reports, 14(1), 1-10. Article 31630. Alblas, D., Vos, I. N., Lipplaa, M. M., Brune, C., van der Schaaf, I. C., Velthuis, M. R. E., Velthuis, B. K., Kuijf, H. J., Ruigrok, Y. M. & Wolterink, J. M.https://doi.org/10.1038/s41598-024-80574-0Automatic virtual reconstruction of acetabular fractures using a statistical shape model (2024)European Journal of Trauma and Emergency Surgery, 50(6), 2925-2936. van Veldhuizen, W. A., van Noortwijk, R., Meesters, A. M. L., ten Duis, K., Schuurmann, R. C. L., de Vries, J. P. P. M., Wolterink, J. M. & IJpma, F. F. A.https://doi.org/10.1007/s00068-024-02615-7CAFLOW: Conditional autoregressive flows (2024)Foundations of Data Science, 6(4), 553-583. Batzolis, G., Carioni, M., Etmann, C., Afyouni, S., Kourtzi, Z. & Schönlieb, C. B.https://doi.org/10.3934/fods.2024028Dissecting SOX9 dynamics reveals its differential regulation in osteoarthritis (2024)Journal of cellular physiology, 239(12). Article e31443. Govindaraj, K., Kannan, S., Coutinho de Almeida, R., Jansen Klomp, L., Karperien, M., Meulenbelt, I. & Post, J. N.https://doi.org/10.1002/jcp.31443Dyadic Partition-Based Training Schemes for TV/TGV Denoising (2024)Journal of Mathematical Imaging and Vision, 66(6), 1070-1108. Davoli, E., Ferreira, R., Fonseca, I. & Iglesias, J. A.https://doi.org/10.1007/s10851-024-01213-xExact sparse representation recovery in signal demixing and group BLASSO (2024)Proceedings in Applied Mathematics and Mechanics. Carioni, M. & Grande, L. D.https://doi.org/10.1002/pamm.202400156Neural fields for 3D tracking of anatomy and surgical instruments in monocular laparoscopic video clips (2024)Healthcare Technology Letters, 11(6), 411-417. Gerats, B. G. A., Wolterink, J. M., Mol, S. P. & Broeders, I. A. M. J.https://doi.org/10.1049/htl2.12113RDA-INR: Riemannian Diffeomorphic Autoencoding via Implicit Neural Representations (2024)SIAM journal on imaging sciences, 17(4), 2302 - 2330. Dummer, S., Brune, C. & Strisciuglio, N.https://doi.org/10.1137/24M1644730Embeddings between Barron spaces with higher-order activation functions (2024)Applied and Computational Harmonic Analysis, 73. Article 101691. Heeringa, T. J., Spek, L., Schwenninger, F. L. & Brune, C.https://doi.org/10.1016/j.acha.2024.101691Gaussian process learning of nonlinear dynamics (2024)Communications in Nonlinear Science and Numerical Simulation, 138. Article 108184. Ye, D. & Guo, M.https://doi.org/10.1016/j.cnsns.2024.108184Machine Learning Based Prediction of Post-operative Infrarenal Endograft Apposition for Abdominal Aortic Aneurysms (2024)European journal of vascular and endovascular surgery, 68(5), 568-576. Veldhuizen, W. A. v., Vries, J.-P. P. M. d., Tuinstra, A., Zuidema, R., IJpma, F. F. A., Wolterink, J. M., Schuurmann, R. C. L., Antoniou, G. A., Balm, R., Kropman, R. H. J. & Sambeek, M. R. H. M. v.https://doi.org/10.1016/j.ejvs.2024.07.003A Statistical Shape Model of Infrarenal Aortic Necks in Patients With and Without Late Type Ia Endoleak After Endovascular Aneurysm Repair (2024)Journal of Endovascular Therapy, 31(5), 882-891. van Veldhuizen, W. A., Schuurmann, R. C. L., Zuidema, R., Geraedts, A. C. M., IJpma, F. F. A., Kropman, R. H. J., Antoniou, G. A., van Sambeek, M. R. H. M., Balm, R., Wolterink, J. M. & de Vries, J. P. P. M.https://doi.org/10.1177/15266028221149913Automated multiclass segmentation, quantification, and visualization of the diseased aorta on hybrid PET/CT–SEQUOIA (2024)Medical physics, 51(6), 4297-4310. van Praagh, G. D., Nienhuis, P. H., Reijrink, M., Davidse, M. E. J., Duff, L. M., Spottiswoode, B. S., Mulder, D. J., Prakken, N. H. J., Scarsbrook, A. F., Morgan, A. W., Tsoumpas, C., Wolterink, J. M., Mouridsen, K. B., Borra, R. J. H., Sinha, B. & Slart, R. H. J. A.https://doi.org/10.1002/mp.16967Graph neural networks for automatic extraction and labeling of the coronary artery tree in CT angiography (2024)Journal of medical imaging, 11(3). Article 034001. Hampe, N., van Velzen, S. G. M., Wolterink, J. M., Collet, C., Henriques, J. P. S., Planken, N. & Išgum, I.https://doi.org/10.1117/1.JMI.11.3.034001Asymptotic linear convergence of fully-corrective generalized conditional gradient methods (2024)Mathematical programming, 205(1-2), 135-202. Bredies, K., Carioni, M., Fanzon, S. & Walter, D.https://doi.org/10.1007/s10107-023-01975-zMesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall (2024)Computers in biology and medicine, 173. Article 108328. Suk, J., de Haan, P., Lippe, P., Brune, C. & Wolterink, J. M.https://doi.org/10.1016/j.compbiomed.2024.108328The effect of propofol on effective brain networks (2024)Clinical neurophysiology, 161(5), 222-230. van Blooijs, D., Blok, S., Huiskamp, G. J. M., Van Eijsden, P., Meijer, H. G. E. & Leijten, F. S. S.https://doi.org/10.1016/j.clinph.2024.01.012Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI (2024)Computer methods and programs in biomedicine, 246. Article 108057. Saitta, S., Carioni, M., Mukherjee, S., Schönlieb, C. B. & Redaelli, A.https://doi.org/10.1016/j.cmpb.2024.108057Increased Intracranial Arterial Pulsatility and Microvascular Brain Damage in Pseudoxanthoma Elasticum (2024)American journal of neuroradiology, 45(4), 386-392. Bartstra, J. W., van den Beukel, T., Kranenburg, G., Geurts, L. J., den Harder, A. M., Witkamp, T., Wolterink, J. M., Zwanenburg, J. J. M., van Valen, E., Koek, H. L., Mali, W. P. T. M., de Jong, P. A., Hendrikse, J. & Spiering, W.https://doi.org/10.3174/ajnr.A8212Quantitative analysis of aortic Na[18F]F uptake in macrocalcifications and microcalcifications in PET/CT scans (2024)Medical physics, 51(4), 2611-2620. van Praagh, G. D., Davidse, M. E. J., Wolterink, J. M. & Slart, R. H. J. A.https://doi.org/10.1002/mp.16787Weak coupling of neurons enables very high-frequency and ultra-fast oscillations through the interplay of synchronized phase-shifts (2024)Network Neuroscience, 8(1), 293-318. Přibylová, L., Sevcik, J., Eclerova, V., Klimes, P., Brazdil, M. & Meijer, H. G. E.https://doi.org/10.1162/netn_a_00351CoNeS: Conditional neural fields with shift modulation for multi-sequence MRI translation (2024)The journal Machine Learning for Biomedical Imaging, 2(special issue for Generative Models). Chen, Y., Staring, M., Neve, O. M., Romeijn, S. R., Hensen, E. F., Verbist, B. M., Wolterink, J. M. & Tao, Q.https://doi.org/10.59275/j.melba.2024-d61gMulti-fidelity reduced-order surrogate modelling (2024)Proceedings of the Royal Society of London A. Mathematical, physical and engineering sciences, 480(2283). Article 20230655. Conti, P., Guo, M., Manzoni, A., Frangi, A., Brunton, S. L. & Kutz, J. N.https://doi.org/10.1098/rspa.2023.0655Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshots (2024)Journal of computational physics, 497. Article 112639. Ye, D., Krzhizhanovskaya, V. & Hoekstra, A. G.https://doi.org/10.1016/j.jcp.2023.112639Bifurcation Analysis of Bogdanov-Takens Bifurcations in Delay Differential Equations (2024)SIAM journal on applied dynamical systems, 23(1), 553-591. Bosschaert, M. M. & Kuznetsov, Y. A.https://doi.org/10.1137/22M1527532Conceptualizing the Sample Mean: Insights for Computer Engineering Students in the Learning Process (2024)IEEE transactions on education, 67(4), 574-581. Kula, F., Litvak, N. & Craig, T. S.https://doi.org/10.1109/TE.2024.3376795Generative modeling of living cells with SO(3)-equivariant implicit neural representations (2024)Medical image analysis, 91. Article 102991. Wiesner, D., Suk, J., Dummer, S., Nečasová, T., Ulman, V., Svoboda, D. & Wolterink, J. M.https://doi.org/10.1016/j.media.2023.102991Hopf Bifurcations of Two Population Neural Fields on the Sphere with Diffusion and Distributed Delays (2024)SIAM journal on applied dynamical systems, 23(3), 1909-1945. Spek, L., van Gils, S. A., Kuznetsov, Y. A. & Polner, M.https://doi.org/10.1137/23M1554011Interplay between Normal Forms and Center Manifold Reduction for Homoclinic Predictors near Bogdanov-Takens Bifurcation (2024)SIAM journal on applied dynamical systems, 23(1), 410-439. Bosschaert, M. M. & Kuznetsov, Y. A.https://doi.org/10.1137/22M151354X
Chapter
Vestibular Schwannoma Growth Prediction from Longitudinal MRI by Time-Conditioned Neural Fields (2024)In Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 (pp. 508-518). Article Chapter 48 (Medical Image Computing and Computer Assisted Intervention – MICCAI 2024; Vol. 15003). Springer. Chen, Y., Wolterink, J. M., Neve, O. M., Romeijn, S. R., Verbist, B. M., Hensen, E. F., Tao, Q. & Staring, M.https://doi.org/10.1007/978-3-031-72384-1_48Forced to improve: open book and open internet assessment in vector calculus (2024)In Takeaways from Teaching through a Pandemic. Practical Examples of Lasting Value in Tertiary Mathematics Education (pp. 81-88). Routledge. Craig, T. S. & Akkaya, T.The unexpected consequences of replacing corridor chats with an online community of practice (2024)In Takeaways from Teaching through a Pandemic. Practical Examples of Lasting Value in Tertiary Mathematics Education (pp. 177-183). Routledge. Craig, T. S., Campbell, A., Mofolo-Mbokane, B. & Padayachee, P.
Conference article
CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning (2024)Proceedings ACM International Conference on Autonomous Agents and Multiagent Systems, 2024-May, 1664-1672. Sauter, A., Botteghi, N., Acar, E. & Plaat, A.
Conference contribution
Brain-Shift: Unsupervised Pseudo-Healthy Brain Synthesis for Novel Biomarker Extraction in Chronic Subdural Hematoma (2024)In Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 - 27th International Conference, Proceedings (pp. 34-44) (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15002 LNCS). Springer. Imre, B., Thibeau-Sutre, E., Reimer, J., Kho, K. & Wolterink, J. M.https://doi.org/10.1007/978-3-031-72069-7_4Fourier-Basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification (2024)In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 17763-17772). Article 10655510. IEEE. Vaish, P., Wang, S. & Strisciuglio, N.https://doi.org/10.1109/CVPR52733.2024.01682Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI (2024)In 2024 IEEE International Symposium on Biomedical Imaging (ISBI): 27-30 May, 2024 - Athens, Greece, Megaron Athens International Conference Centre (pp. 1-5). Article 10635502. IEEE. Laso, P., Cerri, S., Sorby-Adams, A., Guo, J., Mateen, F., Goebl, P., Wu, J., Liu, P., Li, H. B., Young, S. I., Billot, B., Puonti, O., Sze, G., Payabavash, S., DeHavenon, A., Sheth, K. N., Rosen, M. S., Kirsch, J., Strisciuglio, N., … Iglesias, J. E.https://doi.org/10.1109/ISBI56570.2024.10635502Resolution-Invariant Medical Image Segmentation Using Fourier Neural Operators (2024)In Medical Image Understanding and Analysis - 28th Annual Conference, MIUA 2024, Proceedings (pp. 127-142) (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14860 LNCS). Springer. Liu, L., Veldhuis, R. & Brune, C.https://doi.org/10.1007/978-3-031-66958-3_10Recent advances in the open-source ClinicaDL software for reproducible neuroimaging with deep learning (2024)In SPIE Medical Imaging 2024: Image Processing (Proceedings of SPIE; Vol. 12926). SPIE. Hassanaly, R., Brianceau, C., Diaz, M., Loizillon, S., Thibeau-Sutre, E., Cassereau, N., Colliot, O. & Burgos, N.https://doi.org/10.1117/12.3006039Bridging Course: Why, How, and First Impressions (2024)In INDRUM2024 : Fifth conference of the International Network for Didactic Research in University Mathematics (pp. 155-164). Lanting, L. S., Kula, F., ten Klooster, L. & van der Zaag, H.LaB-GATr: Geometric Algebra Transformers for Large Biomedical Surface and Volume Meshes (2024)In Medical Image Computing and Computer Assisted Intervention – MICCAI 2024: 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part XII (pp. 185-195) (Lecture Notes in Computer Science; Vol. 15012). Springer. Suk, J., Imre, B. & Wolterink, J. M.https://doi.org/10.1007/978-3-031-72390-2_18
Dataset
Course materials for Linear Structures 1 (2024)[Dataset Types › Dataset]. Zenodo. Litvak, N., Lanting, L. S. & Weedage, L.https://doi.org/10.5281/zenodo.12779749Application of large language models in radiology: evaluating longitudinal diagnostic yield of imaging for abdominal pain. (2024)[Dataset Types › Dataset]. Zenodo. Dasselaar, S. G. W., von Brucken Fock, Y., Ramselaar, H., Geerdink, J., Wolterink, J. M. & Olthof, A. W.https://doi.org/10.5281/zenodo.11003068AAA-100: A Curated Dataset of 3D Watertight Abdominal Aortic Aneurysm Models (2024)[Dataset Types › Dataset]. Zenodo. Rygiel, P., Alblas, D., Brune, C., Smorenburg, S., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.5281/zenodo.10932956Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification: CIFAR-10 models (2024)[Dataset Types › Dataset]. Zenodo. Vaish, P., Wang, S. & Strisciuglio, N.https://doi.org/10.48550/arXiv.2403.01944
Meeting Abstract
Exploring Neural Correlates of Cognitive Awareness across the Alzheimer’s Disease Continuum: A Multimodal Study (2024)Alzheimer's & dementia, 20(S3). Article e089327. Cacciamani, F., Houot, M., Thibeau-Sutre, E., Tezenas du Montcel, S. & Migliaccio, R.https://doi.org/10.1002/alz.089327
PhD Thesis - Research UT, graduation UT
Anatomy-aided deep learning for medical image segmentation with application to epicardial adipose tissue (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Liu, L.https://doi.org/10.3990/1.9789036562072
Poster
On choosing activation functions for neural fields (2024)[Contribution to conference › Poster] 9th International Conference on Mathematical Neuroscience, ICMNS 2024. Meijer, H. G. E. & van Harten, W.A biophysical model of synaptic transmission during energy deprivation (2024)[Contribution to conference › Poster] 9th International Conference on Mathematical Neuroscience, ICMNS 2024. van Susteren, H.Rda-Inr: Riemannian Diffeomorphic Autoencoding Via Implicit Neural Representations (2024)[Contribution to conference › Poster] SIAM Conference on Imaging Science, IS 2024. Dummer, S., Strisciuglio, N. & Brune, C.
Preprint
Widespread neuronal chaos induced by slow oscillating currents (2024)[Working paper › Preprint]. ArXiv.org. Scully, J., Hinsley, C., Bloom, D., Meijer, H. G. E. & Shilnikov, A. L.https://doi.org/10.48550/arXiv.2411.06304Interpretable and Efficient Data-driven Discovery and Control of Distributed Systems (2024)[Working paper › Preprint]. ArXiv.org. Wolf, F., Botteghi, N., Fasel, U. & Manzoni, A.https://doi.org/10.48550/arXiv.2411.04098A Lipschitz spaces view of infinitely wide shallow neural networks (2024)[Working paper › Preprint]. ArXiv.org. Bartolucci, F., Carioni, M., Iglesias, J. A., Korolev, Y., Naldi, E. & Vigogna, S.https://doi.org/10.48550/arXiv.2410.14591Deep vectorised operators for pulsatile hemodynamics estimation in coronary arteries from a steady-state prior (2024)[Working paper › Preprint]. ArXiv.org. Suk, J., Nannini, G., Rygiel, P., Brune, C., Pontone, G., Redaelli, A. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2410.11920HyperCMR: Enhanced Multi-Contrast CMR Reconstruction with Eagle Loss (2024)[Working paper › Preprint]. ArXiv.org. Xu, R., Özer, C. & Oksuz, I.https://doi.org/10.48550/arXiv.2410.03624A parametric framework for kernel-based dynamic mode decomposition using deep learning (2024)[Working paper › Preprint]. ArXiv.org. Kevopoulos, K. & Ye, D.https://doi.org/10.48550/arXiv.2409.16817Invisible Servoing: a Visual Servoing Approach with Return-Conditioned Latent Diffusion (2024)[Working paper › Preprint]. ArXiv.org. Gerges, B., Bazzana, B., Botteghi, N., Aboudorra, Y. & Franchi, A.https://doi.org/10.48550/arXiv.2409.13337World of Forms: Deformable Geometric Templates for One-Shot Surface Meshing in Coronary CT Angiography (2024)[Working paper › Preprint]. ArXiv.org. van Herten, R. L. M., Lagogiannis, I., Wolterink, J. M., Bruns, S., Meulendijks, E. R., Dey, D., de Groot, J. R., Henriques, J. P., Planken, R. N., Saitta, S. & Išgum, I.https://doi.org/10.48550/arXiv.2409.11837Sparsifying Parametric Models with L0 Regularization (2024)[Working paper › Preprint]. ArXiv.org. Botteghi, N. & Fasel, U.https://doi.org/10.48550/arXiv.2409.03489Physics-informed graph neural networks for flow field estimation in carotid arteries (2024)[Working paper › Preprint]. ArXiv.org. Suk, J., Alblas, D., Hutten, B. A., Wiegman, A., Brune, C., van Ooij, P. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2408.07110Neural Fields for Continuous Periodic Motion Estimation in 4D Cardiovascular Imaging (2024)[Working paper › Preprint]. ArXiv.org. Garzia, S., Rygiel, P., Dummer, S., Cademartiri, F., Celi, S. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2407.20728Sparsifying dimensionality reduction of PDE solution data with Bregman learning (2024)[Working paper › Preprint]. ArXiv.org. Heeringa, T. J., Brune, C. & Guo, M.https://doi.org/10.48550/arXiv.2406.12672Exact Sparse Representation Recovery in Signal Demixing and Group BLASSO (2024)[Working paper › Preprint]. Carioni, M. & Grande, L. D.https://doi.org/10.48550/arXiv.2406.09922Recurrent Deep Kernel Learning of Dynamical Systems (2024)[Working paper › Preprint]. ArXiv.org. Botteghi, N., Motta, P., Manzoni, A., Zunino, P. & Guo, M.https://doi.org/10.48550/arXiv.2405.19785On extremal points for some vectorial total variation seminorms (2024)[Working paper › Preprint]. ArXiv.org. Bredies, K., Iglesias, J. A. & Walter, D.https://doi.org/10.48550/arXiv.2404.12831Vestibular schwannoma growth prediction from longitudinal MRI by time conditioned neural fields (2024)[Working paper › Preprint]. ArXiv.org. Chen, Y., Wolterink, J. M., Neve, O. M., Romeijn, S. R., Verbist, B. M., Hensen, E. F., Tao, Q. & Staring, M.https://doi.org/10.48550/arXiv.2404.02614Brain-Shift: Unsupervised Pseudo-Healthy Brain Synthesis for Novel Biomarker Extraction in Chronic Subdural Hematoma (2024)[Working paper › Preprint]. ArXiv.org. Imre, B., Thibeau-Sutre, E., Reimer, J., Kho, K. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2403.19415Neural Fields for 3D Tracking of Anatomy and Surgical Instruments in Monocular Laparoscopic Video Clips (2024)[Working paper › Preprint]. ArXiv.org. Gerats, B. G. A., Wolterink, J. M., Mol, S. P. & Broeders, I. A. M. J.https://doi.org/10.48550/arXiv.2403.19265Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation (2024)[Working paper › Preprint]. ArXiv.org. Rygiel, P., Alblas, D., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2403.15314Parametric PDE Control with Deep Reinforcement Learning and Differentiable L0-Sparse Polynomial Policies (2024)[Working paper › Preprint]. ArXiv.org. Botteghi, N. & Fasel, U.https://doi.org/10.48550/arXiv.2403.15267LaB-GATr: geometric algebra transformers for large biomedical surface and volume meshes (2024)[Working paper › Preprint]. ArXiv.org. Suk, J., Imre, B. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2403.07536Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification (2024)[Working paper › Preprint]. ArXiv.org. Vaish, P., Wang, S. & Strisciuglio, N.https://doi.org/10.48550/arXiv.2403.01944Second-order flows for approaching stationary points of a class of non-convex energies via convex-splitting schemes (2024)[Working paper › Preprint]. ArXiv.org. Chen, H., Dong, G., Iglesias, J. A., Liu, W. & Xie, Z.https://doi.org/10.48550/arXiv.2402.12173Core: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning (2024)[Working paper › Preprint]. Sauter, A. W. M., Botteghi, N., Acar, E. & Plaat, A.https://doi.org/10.48550/arXiv.2401.16974
Short survey
The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue (2024)Medical image analysis, 97. Article 103257. Weitz, P., Valkonen, M., Solorzano, L., Carr, C., Kartasalo, K., Boissin, C., Koivukoski, S., Kuusela, A., Rasic, D., Feng, Y., Pouplier, S. S., Sharma, A., Eriksson, K. L., Robertson, S., Marzahl, C., Gatenbee, C. D., Anderson, A. R. A., Wodzinski, M., Jurgas, A., … Rantalainen, M.https://doi.org/10.1016/j.media.2024.103257
Working paper
Denoising Diffusion Planner: Learning Complex Paths from Low-Quality Demonstrations (2024)[Working paper › Working paper]. ArXiv.org. Nikken, M., Botteghi, N., Roozing, W. & Califano, F.https://doi.org/10.48550/arXiv.2410.21497
2023
Article
Data-driven analysis of parametrized acoustic systems in the frequency domain (2023)Applied mathematical modelling, 124, 791-805. Xie, X., Wang, W., Wu, H. & Guo, M.https://doi.org/10.1016/j.apm.2023.08.018Deep Learning–Based Intraoperative Stent Graft Segmentation on Completion Digital Subtraction Angiography During Endovascular Aneurysm Repair (2023)Journal of Endovascular Therapy, 30(6), 822-827. Kappe, K. O., Smorenburg, S. P. M., Hoksbergen, A. W. J., Wolterink, J. M. & Yeung, K. K.https://doi.org/10.1177/15266028221105840Discovering efficient periodic behaviors in mechanical systems via neural approximators (2023)Optimal Control Applications and Methods, 44(6), 3052-3079. Wotte, Y. P., Dummer, S., Botteghi, N., Brune, C., Stramigioli, S. & Califano, F.https://doi.org/10.1002/oca.3025Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression (2023)Computers & mathematics with applications, 149, 1-23. Cicci, L., Fresca, S., Guo, M., Manzoni, A. & Zunino, P.https://doi.org/10.1016/j.camwa.2023.08.016Periodic Center Manifolds for Nonhyperbolic Limit Cycles in ODEs (2023)International journal of bifurcation and chaos in applied sciences and engineering, 33(15). Article 2350184. Lentjes, B., Windmolders, M. & Kuznetsov, Y. A.https://doi.org/10.1142/S0218127423501845Boundedness and Unboundedness in Total Variation Regularization (2023)Applied mathematics and optimization, 88(2). Article 51. Bredies, K., Iglesias, J. A. & Mercier, G.https://doi.org/10.1007/s00245-023-10028-yAn in silico and in vitro human neuronal network model reveals cellular mechanisms beyond NaV1.1 underlying Dravet syndrome (2023)Stem cell reports, 18(8), 1686-1700. Doorn, N., Hugte, E. J. H. v., Ciptasari, U., Mordelt, A., Meijer, H. G. E., Schubert, D., Frega, M., Nadif Kasri, N. & Putten, M. J. A. M. v.https://doi.org/10.1016/j.stemcr.2023.06.003The U-Net Family for Epicardial Adipose Tissue Segmentation and Quantification in Low-Dose CT (2023)Technologies, 11(4). Article 104. Liu, L., Ma, R., van Ooijen, P. M. A., Oudkerk, M., Vliegenthart, R., Veldhuis, R. N. J. & Brune, C.https://doi.org/10.3390/technologies110401043D human pose estimation in multi-view operating room videos using differentiable camera projections (2023)Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 11(4), 1197-1205. Gerats, B. G. A., Wolterink, J. M. & Broeders, I. A. M. J.https://doi.org/10.1080/21681163.2022.2155580Development of a Statistical Shape Model and Assessment of Anatomical Shape Variations in the Hemipelvis (2023)Journal of Clinical Medicine, 12(11). Article 3767. van Veldhuizen, W. A., van der Wel, H., Kuipers, H. Y., Kraeima, J., ten Duis, K., Wolterink, J. M., de Vries, J. P. P. M., Schuurmann, R. C. L. & IJpma, F. F. A.https://doi.org/10.3390/jcm12113767Unsupervised convolutional autoencoders for 4D transperineal ultrasound classification (2023)Journal of medical imaging, 10(1). Article 014004. Van Den Noort, F., Manzini, C., Hofsteenge, M., Sirmacek, B., Van Der Vaart, C. H. & Slump, C. H.https://doi.org/10.1117/1.JMI.10.1.014004Multi-fidelity surrogate modeling using long short-term memory networks (2023)Computer methods in applied mechanics and engineering, 404. Article 115811. Conti, P., Guo, M., Manzoni, A. & Hesthaven, J. S.https://doi.org/10.1016/j.cma.2022.115811External Forces in the Continuum Limit of Discrete Systems with Non-Convex Interaction Potentials: Compactness for a Γ-Development (2023)Journal of Convex Analysis, 30(1), 217-247. Carioni, M., Fischer, J. & Schlömerkemper, A.https://www.heldermann.de/JCA/JCA30/JCA301/jca30013.htm
Book
Elements of Applied Bifurcation Theory (2023)[Book/Report › Book]. Springer. Kuznetsov, Y. A.https://doi.org/10.1007/978-3-031-22007-4
Chapter
Reproducibility in Machine Learning for Medical Imaging (2023)In Machine learning for brain disorders (pp. 631-653) (Neuromethods; Vol. 197). Humana Press. Colliot, O., Thibeau-Sutre, E. & Burgos, N.https://doi.org/10.1007/978-1-0716-3195-9_21SE(3) Symmetry Lets Graph Neural Networks Learn Arterial Velocity Estimation from Small Datasets (2023)In Functional Imaging and Modeling of the Heart: 12th International Conference, FIMH 2023, Lyon, France, June 19–22, 2023, Proceedings (pp. 445-454). Suk, J., Brune, C. & Wolterink, J. M.https://doi.org/10.1007/978-3-031-35302-4_46
Conference contribution
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning (2023)In 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) (pp. 129-138). Article 10350684 (Proceedings IEEE/CVF International Conference on Computer Vision Workshops (ICCVW); Vol. 2023). IEEE. Wang, S., Brune, C., Veldhuis, R. & Strisciuglio, N.https://doi.org/10.1109/ICCVW60793.2023.00020What do neural networks learn in image classification? A frequency shortcut perspective (2023)In 2023 IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 1433-1442). Article 10378114 (Proceedings IEEE/CVF International Conference on Computer Vision (ICCV); Vol. 2023). IEEE. Wang, S., Veldhuis, R., Brune, C. & Strisciuglio, N.https://doi.org/10.1109/ICCV51070.2023.00138Uncertainty-based quality assurance of carotid artery segmentation (2023)In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE) (Accepted/In press). Thibeau-Sutre, E., Alblas, D., Buurman, S., Brune, C. & Wolterink, J. M.Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progression (2023)In Functional Imaging and Modeling of the Heart - 12th International Conference, FIMH 2023, Proceedings (pp. 356-365) (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13958 LNCS). Springer. Alblas, D., Hofman, M., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.1007/978-3-031-35302-4_37How Can Data Augmentation Improve Attribution Maps for Disease Subtype Explainability? (2023)In SPIE Medical Imaging 2023: Image Processing. Article 1246424. SPIE. Thibeau-Sutre, E., Wolterink, J. M., Colliot, O. & Burgos, N.https://doi.org/10.1117/12.2653809Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space (2023)In Computer Analysis of Images and Patterns: 20th International Conference, CAIP 2023, Limassol, Cyprus, September 25–28, 2023, Proceedings (pp. 201-211) (Lecture Notes in Computer Science; Vol. 14185). Springer. Mazilu, I., Wang, S., Dummer, S., Veldhuis, R., Brune, C. & Strisciuglio, N.https://doi.org/10.1007/978-3-031-44240-7_20Dynamic Depth-Supervised NeRF for Multi-view RGB-D Operating Room Videos (2023)In Predictive Intelligence in Medicine : 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Proceedings (pp. 218-230) (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14277). Springer. Gerats, B. G. A., Wolterink, J. M. & Broeders, I. A. M. J.https://doi.org/10.1007/978-3-031-46005-0_19Fourier Descriptor Loss and Polar Coordinate Transformation for Pericardium Segmentation (2023)In Computer Analysis of Images and Patterns: 20th International Conference, CAIP 2023, Limassol, Cyprus, September 25–28, 2023, Proceedings (pp. 119-129) (Lecture Notes in Computer Science; Vol. 14185). Springer. Liu, L., Brune, C. & Veldhuis, R.https://doi.org/10.1007/978-3-031-44240-7_12Local Implicit Neural Representations for Multi-Sequence MRI Translation (2023)In 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2023-April). IEEE. Chen, Y., Staring, M., Wolterink, J. M. & Tao, Q.https://doi.org/10.1109/ISBI53787.2023.10230409
Dataset
Conditional gradients for total variation regularization with PDE constraints: a graph cuts approach (2023)[Dataset Types › Dataset]. Zenodo. Cristinelli, G., Iglesias, J. A. & Walter, D.https://doi.org/10.5281/zenodo.10048384Multi-fidelity reduced-order surrogate modeling (2023)[Dataset Types › Dataset]. Zenodo. Conti, P., Guo, M., Manzoni, A., Frangi, A., Brunton, S. L. & Kutz, J. N.https://doi.org/10.5281/zenodo.8316324
Editorial
Table Mountain Delta: Reflect. Connect. Be inspired! (2023)International Journal of Mathematical Education in Science and Technology, 54(9), 1761-1764. Craig, T. S., Blackman, C. & Oates, G.https://doi.org/10.1080/0020739X.2023.2270241
Paper
Exploring Strategies To Promote Engagement And Active Learning Through Digital Course Design In Engineering Mathematics (2023)[Contribution to conference › Paper] 51st Annual Conference of the European Society for Engineering Education, SEFI 2023. Kula, F., Horstman, E. M., Lanting, L. S. & ten Klooster, L. R.https://doi.org/10.21427/5QFW-PY91
PhD Thesis - Research UT, graduation UT
Analysis of Dynamics of Neural Fields and Neural Networks (2023)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Spek, L.https://doi.org/10.3990/1.9789036554824
Poster
Riemannian Shape Manifold Learning with Applications to Biological Data (2023)[Contribution to conference › Poster] EEMCS Research Networking Day 2023. Dummer, S., Strisciuglio, N. & Brune, C.A biophysical model of neuronal dynamics during energy deprivation (2023)[Contribution to conference › Poster] 6th International BonnBrain<sup>3</sup> Conference 2023<br/>. van Susteren, H.
Preprint
Gaussian process learning of nonlinear dynamics (2023)[Working paper › Preprint]. ArXiv.org. Ye, D. & Guo, M.https://doi.org/10.48550/arXiv.2312.12193Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI (2023)[Working paper › Preprint]. ArXiv.org. Laso, P., Cerri, S., Sorby-Adams, A., Guo, J., Mateen, F., Goebl, P., Wu, J., Liu, P., Li, H., Young, S. I., Billot, B., Puonti, O., Sze, G., Payabavash, S., DeHavenon, A., Sheth, K. N., Rosen, M. S., Kirsch, J., Strisciuglio, N., … Iglesias, J. E.https://doi.org/10.48550/arXiv.2312.05119Learning a Sparse Representation of Barron Functions with the Inverse Scale Space Flow (2023)[Working paper › Preprint]. ArXiv.org. Heeringa, T. J., Roith, T., Brune, C. & Burger, M.https://doi.org/10.48550/arXiv.2312.02671Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging (2023)[Working paper › Preprint]. ArXiv.org. Carioni, M., Mukherjee, S., Tan, H. Y. & Tang, J.https://doi.org/10.48550/arXiv.2311.08972A General Theory for Exact Sparse Representation Recovery in Convex Optimization (2023)[Working paper › Preprint]. ArXiv.org. Carioni, M. & Grande, L. D.https://doi.org/10.48550/arXiv.2311.08072SIRE: scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks (2023)[Working paper › Preprint]. ArXiv.org. Alblas, D., Suk, J. M., Brune, C., Yeung, K. K. & Wolterink, J. M.Conditional gradients for total variation regularization with PDE constraints: a graph cuts approach (2023)[Working paper › Preprint]. ArXiv.org. Cristinelli, G., Iglesias, J. A. & Walter, D.https://doi.org/10.48550/arXiv.2310.19777CoNeS: Conditional neural fields with shift modulation for multi-sequence MRI translation (2023)[Working paper › Preprint]. ArXiv.org. Chen, Y., Staring, M., Neve, O. M., Romeijn, S. R., Hensen, E. F., Verbist, B. M., Wolterink, J. M. & Tao, Q.https://doi.org/10.48550/arXiv.2309.03320Multi-fidelity reduced-order surrogate modeling (2023)[Working paper › Preprint]. ArXiv.org. Conti, P., Guo, M., Manzoni, A., Frangi, A., Brunton, S. L. & Kutz, J. N.https://doi.org/10.48550/arXiv.2309.00325Uncertainty-based quality assurance of carotid artery wall segmentation in black-blood MRI (2023)[Working paper › Preprint]. ArXiv.org. Thibeau-Sutre, E., Alblas, D., Buurman, S., Brune, C. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2308.09538Trajectory Generation, Control, and Safety with Denoising Diffusion Probabilistic Models (2023)[Working paper › Preprint]. ArXiv.org. Botteghi, N., Califano, F., Poel, M. & Brune, C.https://doi.org/10.48550/arXiv.2306.15512The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue (2023)[Working paper › Preprint]. ArXiv.org. Weitz, P., Valkonen, M., Solorzano, L., Carr, C., Kartasalo, K., Boissin, C., Koivukoski, S., Kuusela, A., Rasic, D., Feng, Y., Pouplier, S. S., Sharma, A., Eriksson, K. L., Robertson, S., Marzahl, C., Gatenbee, C. D., Anderson, A. R. A., Wodzinski, M., Jurgas, A., … Rantalainen, M.https://doi.org/10.48550/arXiv.2305.18033Embeddings between Barron spaces with higher order activation functions (2023)[Working paper › Preprint]. Heeringa, T. J., Spek, L., Schwenninger, F. & Brune, C.https://doi.org/10.48550/arXiv.2305.15839Rda-inr: Riemannian Diffeomorphic Autoencoding via Implicit Neural Representations (2023)[Working paper › Preprint]. ArXiv.org. Dummer, S., Strisciuglio, N. & Brune, C.https://doi.org/10.48550/arXiv.2305.12854Bayesian approach to Gaussian process regression with uncertain inputs (2023)[Working paper › Preprint]. ArXiv.org. Ye, D. & Guo, M.PDE-constrained Gaussian process surrogate modeling with uncertain data locations (2023)[Working paper › Preprint]. ArXiv.org. Ye, D., Yan, W., Brune, C. & Guo, M.https://doi.org/10.48550/arXiv.2305.11586Dyadic partition-based training schemes for TV/TGV denoising (2023)[Working paper › Preprint]. ArXiv.org. Davoli, E., Ferreira, R., Fonseca, I. & Iglesias, J. A.https://doi.org/10.48550/arXiv.2305.07150A Survey on the Robustness of Computer Vision Models against Common Corruptions (2023)[Working paper › Preprint]. ArXiv.org. Wang, S., Veldhuis, R., Brune, C. & Strisciuglio, N.https://doi.org/10.48550/arXiv.2305.06024Generative modeling of living cells with SO(3)-equivariant implicit neural representations (2023)[Working paper › Preprint]. ArXiv.org. Wiesner, D., Suk, J., Dummer, S., Nečasová, T., Ulman, V., Svoboda, D. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2304.08960A sparse optimization approach to infinite infimal convolution regularization (2023)[Working paper › Preprint]. ArXiv.org. Bredies, K., Carioni, M., Holler, M., Korolev, Y. & Schönlieb, C.-B.https://doi.org/10.48550/arXiv.2304.08628A neural mass model for the EEG in ischemia (2023)[Working paper › Preprint]. bioRxiv. Kalia, M., Ligtenstein, S. L. B., Meijer, H. G. E. & van Putten, M. J. A. M.https://doi.org/10.1101/2023.04.07.535995Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progression (2023)[Working paper › Preprint]. ArXiv.org. Alblas, D., Hofman, M., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2303.01069Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshots (2023)[Working paper › Preprint]. ArXiv.org. Ye, D., Krzhizhanovskaya, V. & Hoekstra, A. G.Periodic Normal Forms for Bifurcations of Limit Cycles in DDEs (2023)[Working paper › Preprint]. Lentjes, B., Spek, L., Bosschaert, M. M. & Kuznetsov, Y. A.SE(3) symmetry lets graph neural networks learn arterial velocity estimation from small datasets (2023)[Working paper › Preprint]. ArXiv.org. Suk, J., Brune, C. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2302.08780Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression (2023)[Working paper › Preprint]. ArXiv.org. Cicci, L., Fresca, S., Guo, M., Manzoni, A. & Zunino, P.https://doi.org/10.48550/arXiv.2302.08216Local Implicit Neural Representations for Multi-Sequence MRI Translation (2023)[Working paper › Preprint]. ArXiv.org. Chen, Y., Staring, M., Wolterink, J. M. & Tao, Q.https://doi.org/10.48550/arXiv.2302.01031
Working paper
A Joint Data- and Model-Driven Approach Simulating the Behaviour of a Walkalong Glider (2023)[Working paper › Working paper]. Cambridge University Press. Alblas, D., van den Bosch, M., Feigl, Z., Klomp, L. J., Rottschäfer, V., Schwenninger, F., Spek, L., Weedage, L. & Zeijlemaker, S.https://doi.org/10.33774/miir-2023-p957pDigital Foot Models from Sensor Data for Improved Orthopedic Aid Fitting (2023)[Working paper › Working paper]. Carere, G., Geurts, B. J., van 't Hof, B., Holtkamp, F., Luesink, E., Schlottbom, M., Suk, J., Sweering, M. & Wolterink, J. M.https://doi.org/10.33774/miir-2023-mk9wnImplicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI (2023)[Working paper › Working paper]. ArXiv.org. Saitta, S., Carioni, M., Mukherjee, S., Schönlieb, C.-B. & Redaelli, A.https://doi.org/10.48550/arXiv.2302.12835
2022
Abstract
Structure preserving implicit shape encoding via flow regularization (2022)[Contribution to conference › Abstract] Geometric Deep Learning in Medical Image Analysis, GeoMedIA 2022. Dummer, S., Strisciuglio, N. & Brune, C.https://openreview.net/pdf?id=YcjlgyX_Ur1
Article
Deep kernel learning of dynamical models from high-dimensional noisy data (2022)Scientific reports, 12, 21530. Article 21530. Botteghi, N., Guo, M. & Brune, C.https://doi.org/10.1038/s41598-022-25362-4Bayesian operator inference for data-driven reduced-order modeling (2022)Computer methods in applied mechanics and engineering, 402. Article 115336. Guo, M., McQuarrie, S. A. & Willcox, K. E.https://doi.org/10.1016/j.cma.2022.115336Convergence of level sets in fractional Laplacian regularization (2022)Inverse problems, 38(12). Article 124003. Iglesias, J. A. & Mercier, G.https://doi.org/10.1088/1361-6420/ac9805A superposition principle for the inhomogeneous continuity equation with Hellinger–Kantorovich-regular coefficients (2022)Communications in partial differential equations, 47(10), 2023-2069. Bredies, K., Carioni, M. & Fanzon, S.https://doi.org/10.1080/03605302.2022.2109172Internal resonance in a MEMS levitation force resonator (2022)Nonlinear Dynamics, 110(2), 1151–1174. Zamanzadeh, M., Meijer, H. G. E. & Ouakad, H. M.https://doi.org/10.1007/s11071-022-07721-yRegularization graphs—a unified framework for variational regularization of inverse problems (2022)Inverse problems, 38(10). Article 105006. Bredies, K., Carioni, M. & Holler, M.https://doi.org/10.1088/1361-6420/ac668dSuper-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning (2022)IEEE transactions on medical imaging, 41(9), 2532-2542. Blanken, N., Wolterink, J. M., Delingette, H., Brune, C., Versluis, M. & Lajoinie, G.https://doi.org/10.1109/TMI.2022.3166443Energy-Based Error Bound of Physics-Informed Neural Network Solutions in Elasticity (2022)Journal of Engineering Mechanics, 148(8). Article 04022038. Guo, M. & Haghighat, E.https://doi.org/10.1061/(ASCE)EM.1943-7889.0002121Extremal points of total generalized variation balls in 1D: characterization and applications (2022)Journal of Convex Analysis, 29(4), 1251-1290. Iglesias, J. A. & Walter, D.https://www.heldermann.de/JCA/JCA29/JCA294/jca29068.htmDynamics of delayed neural field models in two-dimensional spatial domains (2022)Journal of differential equations, 317, 439-473. Spek, L., Dijkstra, K., Gils, S. A. v. & Polner, M.https://doi.org/10.1016/j.jde.2022.02.002A Statistical Shape Model of the Morphological Variation of the Infrarenal Abdominal Aortic Aneurysm Neck (2022)Journal of Clinical Medicine, 11(6). Article 1687. van Veldhuizen, W. A., Schuurmann, R. C. L., Ijpma, F. F. A., Kropman, R. H. J., Antoniou, G. A., Wolterink, J. M. & de Vries, J. P. P. M.https://doi.org/10.3390/jcm11061687Forced to improve: open book and open internet assessment in vector calculus (2022)International Journal of Mathematical Education in Science and Technology, 53(3), 639-646. Craig, T. S. & Akkaya, T.https://doi.org/10.1080/0020739X.2021.1977403The unexpected consequences of replacing corridor chats with an online community of practice (2022)International Journal of Mathematical Education in Science and Technology, 53(3), 745-751. Campbell, A. L., Craig, T. S., Mofolo-Mbokane, B. & Padayachee, P.https://doi.org/10.1080/0020739X.2021.1985179Design principles for final answer assessment in linear algebra: Implications for digital testing (2022)Teaching Mathematics and its Applications, 41(4), 280–291. Veale, A. J. & Craig, T. S.https://doi.org/10.1093/teamat/hrac002AI-Based Quantification of Planned Radiation Therapy Dose to Cardiac Structures and Coronary Arteries in Patients With Breast Cancer (2022)International journal of radiation: Oncology - Biology - Physics, 112(3), 611-620. van Velzen, S. G. M., Bruns, S., Wolterink, J. M., Leiner, T., Viergever, M. A., Verkooijen, H. M. & Išgum, I.https://doi.org/10.1016/j.ijrobp.2021.09.009Deep learning-based whole-heart segmentation in 4D contrast-enhanced cardiac CT (2022)Computers in biology and medicine, 142. Article 105191. Bruns, S., Wolterink, J. M., Boogert, T. P. W. v. d., Runge, J. H., Bouma, B. J., Henriques, J. P., Baan, J., Viergever, M. A., Planken, R. N. & Išgum, I.https://doi.org/10.1016/j.compbiomed.2021.105191A unified physiological framework of transitions between seizures, sustained ictal activity and depolarization block at the single neuron level (2022)Journal of computational neuroscience, 50(1), 33-49. Depannemaecker, D., Ivanov, A., Lillo, D., Spek, L., Bernard, C. & Jirsa, V.https://doi.org/10.1007/s10827-022-00811-1Multi-fidelity regression using artificial neural networks: Efficient approximation of parameter-dependent output quantities (2022)Computer methods in applied mechanics and engineering, 389. Article 114378. Guo, M., Manzoni, A., Amendt, M., Conti, P. & Hesthaven, J. S.https://doi.org/10.1016/j.cma.2021.114378Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle (2022)AI & society, 38(4), 1465-1484. Borsci, S., Lehtola, V. V., Nex, F. C., Yang, M. Y., Augustijn, P. W. M., Bagheriye, L., Brune, C., Kounadi, O., Li, J. J., Rebelo Moreira, J. L., Van der Nagel, J., Veldkamp, B. P., Le, D. V., Wang, M., Wijnhoven, F., Wolterink, J. M. & Zurita-Milla, R.https://doi.org/10.1007/s00146-021-01383-x
Chapter
Implicit Neural Representations for Generative Modeling of Living Cell Shapes (2022)In Medical Image Computing and Computer Assisted Intervention – MICCAI 2022: 25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part IV (pp. 58-67) (Lecture Notes in Computer Science; Vol. 13434). Springer. Wiesner, D., Suk, J., Dummer, S., Svoboda, D. & Wolterink, J. M.https://doi.org/10.1007/978-3-031-16440-8_6
Conference article
Implicit Neural Representations for Deformable Image Registration (2022)Proceedings of Machine Learning Research, 172, 1349-1359. Wolterink, J. M., Zwienenberg, J. C. & Brune, C.
Conference contribution
Self-supervised Learning Through Colorization for Microscopy Images (2022)In Image Analysis and Processing – ICIAP 2022: 21st International Conference, Lecce, Italy, May 23-27, 2022. Proceedings, Part II (pp. 621-632) (Lecture Notes in Computer Science; Vol. 13232). Springer. Pandey, V., Brune, C. & Strisciuglio, N.https://doi.org/10.1007/978-3-031-06430-2_52Now what? Pedagogical implications of a shift to open book assessment of vector calculus (2022)In Proceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022 (pp. 1903-1909) (IEEE Global Engineering Education Conference, EDUCON; Vol. 2022). IEEE. Craig, T. S., Kula, F. & Akkaya, T.https://doi.org/10.1109/EDUCON52537.2022.9766568Deep Learning-Based Carotid Artery Vessel Wall Segmentation in Black-Blood MRI Using Anatomical Priors (2022)In Medical Imaging 2022: Image Processing. Article 120320Y (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 12032). SPIE. Alblas, D., Brune, C. & Wolterink, J. M.https://doi.org/10.1117/12.2611112Modal interaction in a levitation force MEMS based resonator (2022)In Proceedings of ASME 2021 International Mechanical Engineering Congress and Exposition (IMECE2021). Article V07BT07A064 (ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE); Vol. 7B-2021). American Society of Mechanical Engineers. Zamanzadeh, M., Meijer, H. G. E., Jafarsadeghi-Pournaki, I. & Ouakad, H. M.https://doi.org/10.1115/IMECE2021-72755Frequency Shortcut Learning in Neural Networks (2022)In NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and Applications. Wang, S., Veldhuis, R., Brune, C. & Strisciuglio, N.https://openreview.net/forum?id=zAfUHtSGWwGoing Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling (2022)In Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers: 13th International Workshop, STACOM 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers (pp. 79-90). Alblas, D., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.1007/978-3-031-23443-9_8Mesh convolutional neural networks for wall shear stress estimation in 3D artery models (2022)In Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge: 12th International Workshop, STACOM 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Revised Selected Papers (pp. 93-102). Suk, J. M., de Haan, P., Lippe, P., Brune, C. & Wolterink, J. M.https://doi.org/10.1007/978-3-030-93722-5_11The Increasing Necessity of Skills Diversity in Team Teaching (2022)In SEFI 2022 50th Annual Conference of The European Society for Engineering Education: Towards a new future in engineering education, new scenarios that European alliances of tech universities open up (pp. 1898-1902). Artes Gráficas Torres S.L.. Craig, T. S. & Redeker, S.https://www.sefi.be/wp-content/uploads/2022/12/ebook-sefi-2022-1.pdfTowards Autonomous Pipeline Inspection with Hierarchical Reinforcement Learning (2022)In Robot Intelligence Technology and Applications 6 - Results from the 9th International Conference on Robot Intelligence Technology and Applications (pp. 259-271) (Lecture Notes in Networks and Systems; Vol. 429 LNNS). Springer. Botteghi, N., Grefte, L., Poel, M., Sirmacek, B., Brune, C., Dertien, E. & Stramigioli, S.https://doi.org/10.1007/978-3-030-97672-9_23
PhD Thesis - Research UT, graduation UT
Data, models and transitions in computational neuroscience: Bottom-up and top-down approaches (2022)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Kalia, M.https://doi.org/10.3990/1.9789036554091
Poster
A neural mass model for the EEG in ischemia (2022)[Contribution to conference › Poster] Bridging the Gap: from Brain Mechanics to Brain Dynamics 2022. Kalia, M., Meijer, H. G. E., Ligtenstein, S. L. B. & van Putten, M. J. A. M.Simulating differentiation from iPS cells to chondrocytes (2022)[Contribution to conference › Poster] Bioinformatics & Systems Biology Conference, BioSB 2022. Jansen Klomp, L., Coutinho de Almeida, R., Meulenbelt, I., Post, J. N. & Meijer, H. G. E.Dynamical neural network reconstruction based on stimulation data (2022)[Contribution to conference › Poster] Perturbations In Epilepsy 2022. Meijer, H. G. E., Jansen Klomp, L. F., Hebbink, G. J., van Blooijs, D., Zijlmans, M. & Huiskamp, G. J. M.
Preprint
Discovering Efficient Periodic Behaviours in Mechanical Systems via Neural Approximators (2022)[Working paper › Preprint]. ArXiv.org. Wotte, Y., Dummer, S., Botteghi, N., Brune, C., Stramigioli, S. & Califano, F.https://doi.org/10.48550/arXiv.2212.14253Bifurcations of Neural Fields on the Sphere (2022)[Working paper › Preprint]. Spek, L., Gils, S. A. v., Kuznetsov, Y. A. & Polner, M.Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall (2022)[Working paper › Preprint]. ArXiv.org. Suk, J., de Haan, P., Lippe, P., Brune, C. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2212.05023Depth-Supervised NeRF for Multi-View RGB-D Operating Room Images (2022)[Working paper › Preprint]. Gerats, B. G. A., Wolterink, J. M. & Broeders, I. A. M. J.Dynamic Depth-Supervised NeRF for Multi-View RGB-D Operating Room Images (2022)[Working paper › Preprint]. ArXiv.org. Gerats, B. G. A., Wolterink, J. M. & Broeders, I. A. M. J.https://doi.org/10.48550/arXiv.2211.12436Duality for Neural Networks through Reproducing Kernel Banach Spaces (2022)[Working paper › Preprint]. Spek, L., Heeringa, T. J., Schwenninger, F. L. & Brune, C.https://doi.org/10.48550/arXiv.2211.050203D human pose estimation in multi-view operating room videos using differentiable camera projections (2022)[Working paper › Preprint]. ArXiv.org. Gerats, B. G. A., Wolterink, J. M. & Broeders, I. A. M. J.https://doi.org/10.48550/arXiv.2210.11826Convergence of level sets in fractional Laplacian regularization (2022)[Working paper › Preprint]. ArXiv.org. Iglesias, J. A. & Mercier, G.https://doi.org/10.48550/arXiv.2201.13281Extremal points and sparse optimization for generalized Kantorovich-Rubinstein norms (2022)[Working paper › Preprint]. Carioni, M., Iglesias, J. A. & Walter, D.Deep Kernel Learning of Dynamical Models from High-Dimensional Noisy Data (2022)[Working paper › Preprint]. ArXiv.org. Botteghi, N., Guo, M. & Brune, C.https://doi.org/10.48550/arXiv.2208.12975Unsupervised Representation Learning in Deep Reinforcement Learning: A Review (2022)[Working paper › Preprint]. ArXiv.org. Botteghi, N., Poel, M. & Brune, C.https://doi.org/10.48550/arXiv.2208.14226Multi-fidelity surrogate modeling using long short-term memory networks (2022)[Working paper › Preprint]. ArXiv.org. Conti, P., Guo, M., Manzoni, A. & Hesthaven, J. S.https://doi.org/10.48550/arXiv.2208.03115Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling (2022)[Working paper › Preprint]. Alblas, D., Brune, C., Yeung, K. K. & Wolterink, J. M.Implicit Neural Representations for Generative Modeling of Living Cell Shapes (2022)[Working paper › Preprint]. ArXiv.org. Wiesner, D., Suk, J., Dummer, S., Svoboda, D. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2207.06283Periodic Center Manifolds and Normal Forms for DDEs in the Light of Suns and Stars (2022)[Working paper › Preprint]. Lentjes, B., Spek, L., Bosschaert, M. M. & Kuznetsov, Y. A.Periodic Center Manifolds for DDEs in the Light of Suns and Stars (2022)[Working paper › Preprint]. ArXiv.org. Lentjes, B., Spek, L., Bosschaert, M. M. & Kuznetsov, Y. A.https://doi.org/10.48550/arXiv.2207.02480Extremal points of total generalized variation balls in 1D: characterization and applications (2022)[Working paper › Preprint]. ArXiv.org. Iglesias, J. A. & Walter, D.https://doi.org/10.48550/arXiv.2112.06846Bayesian operator inference for data-driven reduced-order modeling (2022)[Working paper › Preprint]. ArXiv.org. Guo, M., McQuarrie, S. A. & Willcox, K. E.https://doi.org/10.48550/arXiv.2204.10829Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning (2022)[Working paper › Preprint]. ArXiv.org. Blanken, N., Wolterink, J. M., Delingette, H., Brune, C., Versluis, M. & Lajoinie, G.https://doi.org/10.48550/arXiv.2204.04537Boundedness and unboundedness in total variation regularization (2022)[Working paper › Preprint]. ArXiv.org. Bredies, K., Iglesias, J. A. & Mercier, G.https://doi.org/10.48550/arXiv.2203.03264Geometric convergence in fractional Laplacian regularization (2022)[Working paper › Preprint]. ArXiv.org. Iglesias, J. A. & Mercier, G.https://doi.org/10.48550/arXiv.2201.13281
2021
Abstract
A Bayesian formulation of operator inference for non-intrusive reduced order modeling (2021)[Contribution to conference › Abstract] SIAM Conference on Computational Science and Engineering, CSE 2021. Guo, M., McQuarrie, S. A. & Willcox, K. E.Contrast-enhanced single-RF-line simulations and super-resolution microbubble detection using deep learning (2021)[Contribution to conference › Abstract] 26th European Symposium on Ultrasound Contrast Imaging 2021. Blanken, N., Wolterink, J. M., Delingette, H., Brune, C., Versluis, M. & Lajoinie, G. P. R.Bayesian methods for non-intrusive reduced order modeling (2021)[Contribution to conference › Abstract] Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering and Technology, MMLDT-CSET 2021. Guo, M., Hesthaven, J. S., Kast, M., McQuarrie, S. A. & Willcox, K. E.Bayesian operator inference for the reduced order modeling of time-dependent problems (2021)[Contribution to conference › Abstract] 15th Biannual Congress of SIMAI 2021. Guo, M., McQuarrie, S. A. & Willcox, K. E.Bounding discretization errors of physics-informed neural network solutions in elasticity (2021)[Contribution to conference › Abstract] 16th U.S. National Congress on Computational Mechanics 2021. Guo, M. & Haghighat, E.
Article
Glial chloride homeostasis under transient ischemic stress (2021)Frontiers in cellular neuroscience, 15. Article 735300. Engels, M., Kalia, M., Rahmati, S., Petersilie, L., Kovermann, P., van Putten, M. J. A. M., Rose, C. R., Meijer, H. G. E., Gensch, T. & Fahlke, C.https://doi.org/10.3389/fncel.2021.735300On the role of arkypallidal and prototypical neurons for phase transitions in the external pallidum (2021)The Journal of neuroscience, 41(31), 6673-6683. Gast, R., Gong, R., Schmidt, H., Meijer, H. G. E. & Knosche, T.https://doi.org/10.1523/JNEUROSCI.0094-21.2021Directionality of corticomuscular coupling in essential tremor and cortical myoclonic tremor (2021)Clinical neurophysiology, 132(8), 1878-1886. Sharifi, S., Luft, F., Potgieter, S., Heida, T., Mugge, W., Schouten, A. C., Bour, L. J. & Rootselaar, A. F. v.https://doi.org/10.1016/j.clinph.2021.04.011Bistability and Stabilization of Human Visual Perception under Ambiguous Stimulation (2021)Nonlinear Dynamics, Psychology, and Life Sciences, 25(3), 297-307. Govaerts, W., Kuznetsov, Y. A., Meijer, H. G. E., Neirynck, N. & van Wezel, R. J. A.Ion dynamics at the energy-deprived tripartite synapse (2021)PLoS Computational Biology, 17(6). Article e1009019. Kalia, M., Meijer, H. G. E., van Gils, S. A., van Putten, M. J. A. M. & Rose, C. R.https://doi.org/10.1371/journal.pcbi.1009019Mechanisms Underlying Vascular Endothelial Growth Factor Receptor Inhibition-Induced Hypertension: The HYPAZ Trial (2021)Hypertension, 77(5), 1591-1599. Mäki-Petäjä, K. M., McGeoch, A., Yang, L. L., Hubsch, A., McEniery, C. M., Meyer, P. A. R., Mir, F., Gajendragadkar, P., Ramenatte, N., Anandappa, G., Santos Franco, S., Bond, S. J., Schönlieb, C. B., Boink, Y., Brune, C., Wilkinson, I. B., Jodrell, D. I. & Cheriyan, J.https://doi.org/10.1161/HYPERTENSIONAHA.120.16454Generative Adversarial Networks: A Primer for Radiologists (2021)Radiographics, 41(3), 840-857. Wolterink, J. M., Mukhopadhyay, A., Leiner, T., Vogl, T. J., Bucher, A. M. & Išgum, I.https://doi.org/10.1148/rg.2021200151Six months vitamin K treatment does not affect systemic arterial calcification or bone mineral density in diabetes mellitus 2 (2021)European Journal of Nutrition, 60(3), 1691-1699. Bartstra, J. W., Draaisma, F., Zwakenberg, S. R., Lessmann, N., Wolterink, J. M., van der Schouw, Y. T., de Jong, P. A. & Beulens, J. W. J.https://doi.org/10.1007/s00394-020-02412-z(INVITED) Homoclinic puzzles and chaos in a nonlinear laser model (2021)Communications in Nonlinear Science and Numerical Simulation, 93. Article 105503. Pusuluri, K., Meijer, H. G. E. & Shilnikov, A. L.https://doi.org/10.1016/j.cnsns.2020.105503
Chapter
Uncertainty quantification for physics-informed deep learning (2021)In Mathematics: Key Enabling Technology for Scientific Machine Learning (pp. 47-51). Guo, M. & Brune, C.https://platformwiskunde.nl/wp-content/uploads/2021/11/Math_KET_SciML.pdfPredictive Monitoring of Large-Scale Engineering Assets Using Machine Learning Techniques and Reduced-Order Modeling (2021)In Structural health monitoring based on data science techniques (pp. 185-205) (Structural Integrity (STIN); Vol. 21). Springer. Bigoni, C., Guo, M. & Hesthaven, J. S.https://doi.org/10.1007/978-3-030-81716-9_9
Conference article
Rlsnake: A hybrid reinforcement learning approach for road detection (2021)International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 43(B3-2021), 39-45. Botteghi, N., Sirmacek, B. & Ünsalan, C.https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-39-2021CURIOSITY-DRIVEN REINFORCEMENT LEARNING AGENT for MAPPING UNKNOWN INDOOR ENVIRONMENTS (2021)ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 5(1), 129-136. Botteghi, N., Sirmacek, B., Poel, M., Brune, C. & Schulte, R.https://doi.org/10.5194/isprs-annals-V-1-2021-129-2021
Conference contribution
Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces (2021)In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021 (pp. 190-197) (IEEE International Conference on Intelligent Robots and Systems). IEEE. Botteghi, N., Alaa, K., Poel, M., Sirmaçek, B., Brune, C., Mersha, A. & Stramigioli, S.https://doi.org/10.1109/IROS51168.2021.9635936Open book vector calculus assessment: suggested design principles (2021)In Proceedings SEFI 49th Annual Conference 2021: Blended Learning in Engineering Education: challenging, enlightening – and lasting? (pp. 1365-1369). Craig, T. S.A System for Efficient Path Planning and Target Assignment for Robotic Swarms in Agriculture (2021)In IoT '21: Proceedings of the 11th International Conference on the Internet of Things (pp. 158-164). Association for Computing Machinery. Postmes, J., Botteghi, N., Sirmacek, B. & Kamilaris, A.https://doi.org/10.1145/3494322.3494352Low Dimensional State Representation Learning with Reward-shaped Priors (2021)In 2020 25th International Conference on Pattern Recognition (ICPR) (pp. 3736-3743). Article 9412421. Botteghi, N., Obbink, R., Geijs, D., Poel, M., Sirmacek, B., Brune, C., Mersha, A. & Stramigioli, S.https://doi.org/10.1109/ICPR48806.2021.9412421Automatic whole-heart segmentation in 4D TAVI treatment planning CT (2021)In Medical Imaging 2021: Image Processing (SPIE Conference Proceedings; Vol. 11596). SPIE. Bruns, S., Wolterink, J. M., Van Den Boogert, T. P. W., Henriques, J. P., Baan, J., Planken, R. N., Išgum, I., Landman, B. A. & Išgum, I.https://doi.org/10.1117/12.2581020Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis (2021)In Medical Imaging 2021: Image Processing (SPIE Cofnerence Proceedings; Vol. 11596). SPIE. Zreik, M., Hampe, N., Leiner, T., Khalili, N., Wolterink, J. M., Voskuil, M., Viergever, M. A., Išgum, I., Landman, B. A. & Išgum, I.https://doi.org/10.1117/12.2580847Graph attention networks for segment labeling in coronary artery trees (2021)In Medical Imaging 2021 (Proceedings of SPIE; Vol. 11596). SPIE. Hampe, N., Wolterink, J. M., Collet, C., Planken, R. N., Išgum, I., Landman, B. A. & Išgum, I.https://doi.org/10.1117/12.2581219Hamiltonian boussinesq simulation of wave-ship interaction above sloping bottom (2021)In Proceedings of the 31st International Ocean and Polar Engineering Conference, ISOPE 2021 (pp. 1702-1709) (Proceedings of the International Offshore and Polar Engineering Conference). International Society of Offshore and Polar Engineers. Kurnia, R. & van Groesen, E.
Dataset
Normal Form Autoencoder, data associated with the publication: ‘Learning normal form autoencoders for data-driven discovery of universal, parameter-dependent governing equations’ (2021)[Dataset Types › Dataset]. 4TU.Centre for Research Data. Kalia, M., Meijer, H. G. E., Brunton, S. L., Kutz, J. N. & Brune, C.
PhD Thesis - Research UT, graduation UT
Data-driven reconstruction methods for photoacoustic tomography: Learning structures by structured learning (2021)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Boink, Y. E.https://doi.org/10.3990/1.9789036550871
Preprint
Deep Learning-Based Carotid Artery Vessel Wall Segmentation in Black-Blood MRI Using Anatomical Priors (2021)[Working paper › Preprint]. ArXiv.org. Alblas, D., Brune, C. & Wolterink, J. M.https://arxiv.org/abs/2112.01137Mesh convolutional neural networks for wall shear stress estimation in 3D artery models (2021)[Working paper › Preprint]. ArXiv.org. Suk, J., de Haan, P., Lippe, P., Brune, C. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2109.04797Towards Autonomous Pipeline Inspection with Hierarchical Reinforcement Learning (2021)[Working paper › Preprint]. Botteghi, N., Grefte, L., Poel, M., Sirmacek, B., Brune, C., Dertien, E. & Stramigioli, S.Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces (2021)[Working paper › Preprint]. ArXiv.org. Botteghi, N., Alaa, K., Poel, M., Sirmacek, B., Brune, C., Mersha, A. & Stramigioli, S.https://doi.org/10.48550/arXiv.2107.01667Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics (2021)[Working paper › Preprint]. ArXiv.org. Botteghi, N., Poel, M., Sirmacek, B. & Brune, C.End-to-end reconstruction meets data-driven regularization for inverse problems (2021)[Working paper › Preprint]. ArXiv.org. Mukherjee, S., Carioni, M., Öktem, O. & Schönlieb, C.-B.https://doi.org/10.48550/arXiv.2106.03538
Review article
Anatomy-aided deep learning for medical image segmentation: A review (2021)Physics in medicine and biology, 66(11). Article 11TR01. Liu, L., Wolterink, J. M., Brune, C. & Veldhuis, R. N. J.https://doi.org/10.1088/1361-6560/abfbf4
Working paper
A brief note on understanding neural networks as Gaussian processes (2021)[Working paper › Working paper]. ArXiv.org. Guo, M.https://arxiv.org/abs/2107.11892Learning normal form autoencoders for data-driven discovery of universal, parameter-dependent governing equations (2021)[Working paper › Working paper]. ArXiv.org. Kalia, M., Brunton, S. L., Meijer, H. G. E., Brune, C. & Kutz, J. N.https://arxiv.org/abs/2106.05102Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities (2021)[Working paper › Working paper]. ArXiv.org. Guo, M., Manzoni, A., Amendt, M., Conti, P. & Hesthaven, J. S.https://doi.org/10.48550/arXiv.2102.13403
2020
Article
Neural field models with transmission delays and diffusion (2020)Journal of mathematical neuroscience, 10. Article 21. Spek, L., Kuznetsov, Y. A. & van Gils, S. A.https://doi.org/10.1186/s13408-020-00098-5Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images (2020)IEEE transactions on medical imaging, 39(12), 4011-4022. Article 9139480. Noothout, J. M. H., De Vos, B. D., Wolterink, J. M., Postma, E. M., Smeets, P. A. M., Takx, R. A. P., Leiner, T., Viergever, M. A. & Išgum, I.https://doi.org/10.1109/TMI.2020.3009002On analysis of inputs triggering large nonlinear neural responses: Slow-fast dynamics in the Wendling neural mass model (2020)Communications in Nonlinear Science and Numerical Simulation, 83. Article 105103. Hebbink, J., van Gils, S. A. & Meijer, H. G. E.https://doi.org/10.1016/j.cnsns.2019.105103Deep learning of circulating tumour cells (2020)Nature Machine Intelligence, 2(2), 124-133. Zeune, L. L., Boink, Y. E., van Dalum, G., Nanou, A., de Wit, S., Andree, K. C., Swennenhuis, J. F., van Gils, S. A., Terstappen, L. W. M. M. & Brune, C.https://doi.org/10.1038/s42256-020-0153-xPathological responses to single pulse electrical stimuli in epilepsy: the role of feedforward inhibition (2020)European journal of neuroscience, 51(4), 1122-1136. Hebbink, J., Huiskamp, G. J. M., van Gils, S. A., Leijten, F. S. S. & Meijer, H. G. E.https://doi.org/10.1111/ejn.14562Switching to nonhyperbolic cycles from codimension two bifurcations of equilibria of delay differential equations (2020)SIAM journal on applied dynamical systems, 19(1), 252-303. Bosschaert, M. M., Janssens, S. G. & Kuznetsov, Y. A.https://doi.org/10.1137/19M1243993
Book
Simulation and Synthesis in Medical Imaging (2020)[Book/Report › Book] 5th International Workshop on Simulation and Synthesis in Medical Imaging , SASHIMI 2020. Springer. Burgos, N., Svoboda, D., Wolterink, J. M. & Zhao, C.https://doi.org/10.1007/978-3-030-59520-3
Conference article
Reinforcement learning helps slam: Learning to build maps (2020)International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 43(B4), 329-336. Botteghi, N., Sirmacek, B., Poel, M. & Brune, C.https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-329-2020
Conference contribution
An interdisciplinary eye on mathematics service teaching (2020)In Engaging, Engineering, Education: Book of Abstracts, SEFI 48th Annual Conference University of Twente (online), 20-24 September, 2020 (pp. 995-1003). University of Twente. Meijer, H. G. E. & Craig, T. S.Enhancing service mathematics teaching through strategic alignment (2020)In Engaging, Engineering, Education: Book of Abstracts, SEFI 48th Annual Conference University of Twente (online), 20-24 September, 2020 (pp. 169-179). University of Twente. Craig, T. S.Students' mental constructions of concepts in vector calculus: insights from two universities (2020)In Engaging, Engineering, Education: Book of Abstracts, SEFI 48th Annual Conference University of Twente (online), 20-24 September, 2020 (pp. 1022-1032). University of Twente. Padayachee, P. & Craig, T. S.
Paper
Deep learning of normal form autoencoders for universal, parameter-dependent dynamics (2020)[Contribution to conference › Paper] 1st NeurIPS Workshop on Interpretable Inductive Biases and Physically Structured Learning 2020. Kalia, M., Brunton, S. L., Meijer, H. G. E., Brune, C. & Kutz, J. N.https://inductive-biases.github.io/papers/46.pdf
Preprint
Dynamics of delayed neural field models in two-dimensional spatial domains (2020)[Working paper › Preprint]. ArXiv.org. Spek, L., Polner, M., Dijkstra, K. & van Gils, S. A.https://doi.org/10.48550/arXiv.2009.08362Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images (2020)[Working paper › Preprint]. ArXiv.org. Noothout, J. M. H., de Vos, B. D., Wolterink, J. M., Postma, E. M., Smeets, P. A. M., Takx, R. A. P., Leiner, T., Viergever, M. A. & Išgum, I.https://doi.org/10.48550/arXiv.2007.05295
Working paper
Learned SVD: solving inverse problems via hybrid autoencoding (2020)[Working paper › Working paper]. ArXiv.org. Boink, Y. E. & Brune, C.https://arxiv.org/abs/1912.10840v1Energy-based error bound of physics-informed neural network solutions in elasticity (2020)[Working paper › Working paper]. ArXiv.org. Guo, M. & Haghighat, E.https://arxiv.org/abs/2010.09088
2019
Article
A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction and Segmentation (2019)IEEE transactions on medical imaging, 39(1), 129-139. Article 8734097. Boink, Y. E., Manohar, S. & Brune, C.https://doi.org/10.1109/TMI.2019.2922026A Comparison of Evoked and Non-evoked Functional Networks (2019)Brain topography, 32(3), 405-417. Hebbink, J., van Blooijs, D., Huiskamp, G., Leijten, F. S. S., van Gils, S. A. & Meijer, H. G. E.https://doi.org/10.1007/s10548-018-0692-1
Conference contribution
The Twente educational model in theory and practice: two modules as exemplars (2019)In Swan Delta 2019 Proceedings: The 12th Delta Conference on the teaching and learning of undergraduate mathematics and statistics: reflections of change proceedings (pp. 19 - 28). Western Sydney University. Craig, T. S.https://doi.org/10.26183/5d5f53ed9c926
PhD Thesis - Research UT, graduation UT
Computational Modelling and Electrical Stimulation for Epilepsy Surgery (2019)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Hebbink, J.https://doi.org/10.3990/1.9789036548328
Preprint
Neural Field Models with Transmission Delays and Diffusion (2019)[Working paper › Preprint]. ArXiv.org. Spek, L., Kuznetsov, Y. A. & van Gils, S. A.https://doi.org/10.48550/arXiv.1912.09762
2018
Article
Evoked directional network characteristics of epileptogenic tissue derived from single pulse electrical stimulation (2018)Human brain mapping, 39(11), 4611-4622. van Blooijs, D., Leijten, F. S. S., van Rijen, P. C., Meijer, H. G. E. & Huiskamp, G. J. M.https://doi.org/10.1002/hbm.24309Numerical bifurcation analysis of double +1 multiplier in ℤ3-symmetric maps (2018)Journal of difference equations and applications, 24(9), 1402-1413. Mazrooei-Sebdani, R., Eskandari, Z. & Meijer, H. G. E.https://doi.org/10.1080/10236198.2018.1491558Remarks on homoclinic structure in Bogdanov-Takens map (2018)Journal of difference equations and applications, 24(4), 575-587. Al-Hdaibat, B., Govaerts, W., van Kekem, D. L. & Kuznetsov, Y. A.https://doi.org/10.1080/10236198.2017.1329894
Conference contribution
Spectral AB simulations for coastal and ocean engineering applications (2018)In Proceedings of the Fourth International Conference in Ocean Engineering (ICOE2018) (pp. 207-217) (Lecture Notes in Civil Engineering; Vol. 23). Springer. Kurnia, R., Turnip, P. & van Groesen, E.https://doi.org/10.1007/978-981-13-3134-3_16
2016
Article
A Biophysical Model for Cytotoxic Cell Swelling (2016)The Journal of neuroscience, 36(47), 11881-11890. Dijkstra, K., Hofmeijer, J., van Gils, S. A. & van Putten, M. J. A. M.https://doi.org/10.1523/JNEUROSCI.1934-16.2016
2015
Article
Exploiting pallidal plasticity for stimulation in Parkinson’s disease (2015)Journal of neural engineering, 12(2), 026005. Lourens, M. A. J., Schwab, B., Nirody, J. A., Meijer, H. G. E. & van Gils, S. A.https://doi.org/10.1088/1741-2560/12/2/026005Tracking pattern evolution through extended center manifold reduction and singular perturbations (2015)Physica D, 298-299, 48-67. Sewalt, L., Doelman, A., Meijer, H. G. E., Rottschäfer, V. & Zagaris, A.https://doi.org/10.1016/j.physd.2015.01.006
Dataset
HAWASSI (2015)[Dataset Types › Dataset]. LabMath-Indonesia. van Groesen, E. W. C. & Kurnia, R.
2014
Article
Improved homoclinic predictor for Bogdanov-Takens bifurcation (2014)International journal of bifurcation and chaos in applied sciences and engineering, 24(4), 1450057. Kouznetsov, I. A., Meijer, H. G. E., Al Hdaibat, B. & Govaerts, W.https://doi.org/10.1142/S0218127414500576Travelling waves in a neural field model with refractoriness (2014)Journal of mathematical biology, 68(5), 1249-1268. Meijer, H. G. E. & Coombes, S.https://doi.org/10.1007/s00285-013-0670-x
1998
Letter
Electroencephalography and survival in patients with Alzheimer's disease (1998)Neurology, 51(3), 918-919. Claus, J. J. & Bour, L. J.https://doi.org/10.1212/WNL.51.3.918-b
1991
Conference contribution
Computer simulation of oculomotor control in extrapyramidal disorders (1991)In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society 1991 (pp. 2307-2308) (Proceedings of the Annual Conference on Engineering in Medicine and Biology; Vol. 13). IEEE. Bour, L. J., Wolzak, A., Van't Ent, D., Speelman, J. D. & Ongerboer de Visser, B. W.https://doi.org/10.1109/IEMBS.1991.685014
1987
Meeting Abstract
The cumulative vibratory index of the soleus H-reflex: A study in controls and spastic patients (1987)Clinical neurology and neurosurgery, 89(2), 124-124. Ongerboer de Visser, B. W., Bour, L. J. & Speelman, J. D.https://doi.org/10.1016/0303-8467(87)90193-4
For the overview of output in the previous years, please visit the University of Twente Research Information Portal