Publications

This page shows selected publications of the Computer Vision group. For current listings, see also Google Scholar.

2026

  • Sutton, M., Amunts, K., Dickscheid, T., & Schiffer, C. (2026). Cytoarchitecture in Words: Weakly Supervised Vision-Language Modeling for Human Brain Microscopy (arXiv:2602.23088). arXiv. https://doi.org/10.48550/arXiv.2602.23088
  • Oberstrass, A., Vaca, E., Upschulte, E., Niu, M., Palomero-Gallagher, N., Graessel, D., Schiffer, C., Axer, M., Amunts, K., & Dickscheid, T. (2026). From fibers to cells: Fourier-based registration enables virtual Cresyl violet staining from 3D polarized light imaging. Imaging Neuroscience, 4, IMAG.a.1079. https://doi.org/10.1162/IMAG.a.1079
  • Römer, J., & Dickscheid, T. (2026). Depth-Wise Representation Development Under Blockwise Self-Supervised Learning for Video Vision Transformers (arXiv:2601.09040). arXiv. https://doi.org/10.48550/arXiv.2601.09040

2025

  • Dickscheid, T., Gui, X., Simsek, A. N., Schiffer, C., Mangin, J.-F., Leprince, Y., Jirsa, V., Bjaalie, J. G., Leergaard, T. B., Bludau, S., & Amunts, K. (2025). Siibra: A software tool suite for realizing a Multilevel Human Brain Atlas from complex data resources (p. 2025.05.20.655042). bioRxiv. https://doi.org/10.1101/2025.05.20.655042
  • Schiffer, C., Boztoprak, Z., Kropp, J.-O., Thönnißen, J., Berr, K., Spitzer, H., Amunts, K., & Dickscheid, T. (2025). CytoNet: A Foundation Model for the Human Cerebral Cortex (arXiv:2511.01870). arXiv. https://doi.org/10.48550/arXiv.2511.01870

2024

  • Amunts, K., Axer, M., Banerjee, S., Bitsch, L., Bjaalie, J. G., Brauner, P., Brovelli, A., Calarco, N., Carrere, M., Caspers, S., Charvet, C. J., Cichon, S., Cools, R., Costantini, I., D’Angelo, E. U., De Bonis, G., Deco, G., DeFelipe, J., Destexhe, A., … Zaborszky, L. (2024). The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing. Imaging Neuroscience, 2, 1–35. https://doi.org/10.1162/imag_a_00137
  • Eberhard, D., Balkenhol, S., Köster, A., Follert, P., Upschulte, E., Ostermann, P., Kirschner, P., Uhlemeyer, C., Charnay, I., Preuss, C., Trenkamp, S., Belgardt, B.-F., Dickscheid, T., Esposito, I., Roden, M., & Lammert, E. (2024). Semaphorin-3A regulates liver sinusoidal endothelial cell porosity and promotes hepatic steatosis. Nature Cardiovascular Research, 3(6), 734–753. https://doi.org/10.1038/s44161-024-00487-z
  • Gholivand, A., Korculanin, O., Dahlhoff, K., Babaki, M., Dickscheid, T., & Lettinga, M. P. (2024). Effect of in-plane and out-of-plane bifurcated microfluidic channels on the flow of aggregating red blood cells. Lab on a Chip. https://doi.org/10.1039/D4LC00151F
  • Kropp, J.-O., Schiffer, C., Amunts, K., & Dickscheid, T. (2024). Denoising Diffusion Probabilistic Models for Image Inpainting of Cell Distributions in The Human Brain. 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1–5. https://doi.org/10.1109/ISBI56570.2024.10635384
  • Ma, J., Xie, R., Ayyadhury, S., Ge, C., Gupta, A., Gupta, R., Gu, S., Zhang, Y., Lee, G., Kim, J., Lou, W., Li, H., Upschulte, E., Dickscheid, T., De Almeida, J. G., Wang, Y., Han, L., Yang, X., Labagnara, M., … Wang, B. (2024). The multimodality cell segmentation challenge: Toward universal solutions. Nature Methods. https://doi.org/10.1038/s41592-024-02233-6
  • Nebli, A., Schiffer, C., Niu, M., Palomero-Gallagher, N., Amunts, K., & Dickscheid, T. (2024). Generative Modelling of Cortical Receptor Distributions from Cytoarchitectonic Images in the Macaque Brain. Neuroinformatics. https://doi.org/10.1007/s12021-024-09673-7
  • Oberstrass, A., DeKraker, J., Palomero-Gallagher, N., Muenzing, S. E. A., Evans, A. C., Axer, M., Amunts, K., & Dickscheid, T. (2024). Analyzing Regional Organization of The Human Hippocampus in 3D-PLI Using Contrastive Learning and Geometric Unfolding. 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1–5. https://doi.org/10.1109/ISBI56570.2024.10635467
  • Oberstrass, A., Muenzing, S. E. A., Niu, M., Palomero-Gallagher, N., Schiffer, C., Axer, M., Amunts, K., & Dickscheid, T. (2024). Self-Supervised Representation Learning for Nerve Fiber Distribution Patterns in 3D-PLI. Imaging Neuroscience. https://doi.org/10.1162/imag_a_00351
  • Wang, X., Leprince, Y., Lebenberg, J., Langlet, C., Mohlberg, H., Rivière, D., Auzias, G., Dickscheid, T., Amunts, K., & Mangin, J.-F. (2024). A framework to improve the alignment of individual cytoarchitectonic maps of the Julich-Brain atlas using cortical folding landmarks. Cerebral Cortex, 34(2), bhad538. https://doi.org/10.1093/cercor/bhad538

2023

  • Kleven, H., Gillespie, T. H., Zehl, L., Dickscheid, T., Bjaalie, J. G., Martone, M. E., & Leergaard, T. B. (2023). AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures. Scientific Data, 10(1), Article 1. https://doi.org/10.1038/s41597-023-02389-4
  • Sip, V., Hashemi, M., Dickscheid, T., Amunts, K., Petkoski, S., & Jirsa, V. (2023). Characterization of regional differences in resting-state fMRI with a data-driven network model of brain dynamics. Science Advances, 9(11), eabq7547. https://doi.org/10.1126/sciadv.abq75471
  • Unger, N., Haeck, M., Eickhoff, S. B., Camilleri, J. A., Dickscheid, T., Mohlberg, H., Bludau, S., Caspers, S., & Amunts, K. (2023). Cytoarchitectonic mapping of the human frontal operculum—New correlates for a variety of brain functions. Frontiers in Human Neuroscience, 17, 1087026. https://doi.org/10.3389/fnhum.2023.1087026
  • Zachlod, D., Palomero-Gallagher, N., Dickscheid, T., & Amunts, K. (2023). Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity. Biological Psychiatry, 93(5), 471–479. https://doi.org/10.1016/j.biopsych.2022.09.014

2022

  • Quabs, J., Caspers, S., Schöne, C., Mohlberg, H., Bludau, S., Dickscheid, T., & Amunts, K. (2022). Cytoarchitecture, probability maps and segregation of the human insula. NeuroImage, 260, 119453. https://doi.org/10.1016/j.neuroimage.2022.119453
  • Schirner, M., Domide, L., Perdikis, D., Triebkorn, P., Stefanovski, L., Pai, R., Prodan, P., Valean, B., Palmer, J., Langford, C., Blickensdörfer, A., van der Vlag, M., Diaz-Pier, S., Peyser, A., Klijn, W., Pleiter, D., Nahm, A., Schmid, O., Woodman, M., … Ritter, P. (2022). Brain simulation as a cloud service: The Virtual Brain on EBRAINS. NeuroImage, 251, 118973. https://doi.org/10.1016/j.neuroimage.2022.118973
  • Upschulte, E., Harmeling, S., Amunts, K., & Dickscheid, T. (2022). Contour Proposal Networks for Biomedical Instance Segmentation. Medical Image Analysis, 102371. https://doi.org/10.1016/j.media.2022.1023710
  • Vaca, E., Menzel, M., Amunts, K., Axer, M., & Dickscheid, T. (2022). GORDA: Graph-Based Orientation Distribution Analysis of SLI Scatterometry Patterns of Nerve Fibres. 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1–5. https://doi.org/10.1109/ISBI52829.2022.9761492
  • Van Albada, S. J., Morales-Gregorio, A., Dickscheid, T., Goulas, A., Bakker, R., Bludau, S., Palm, G., Hilgetag, C.-C., & Diesmann, M. (2022). Bringing Anatomical Information into Neuronal Network Models. In M. Giugliano, M. Negrello, & D. Linaro (Eds), Computational Modelling of the Brain (Vol. 1359, pp. 201–234). Springer International Publishing. https://doi.org/10.1007/978-3-030-89439-9_9

2021

  • Paquola, C., Royer, J., Lewis, L. B., Lepage, C., Glatard, T., Wagstyl, K., DeKraker, J., Toussaint, P.-J., Valk, S. L., Collins, D. L., Khan, A., Amunts, K., Evans, A. C., Dickscheid, T., & Bernhardt, B. C. (2021). The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging. eLife, 10, e70119. https://doi.org/10.7554/eLife.70119
  • Schiffer, C., Amunts, K., Harmeling, S., & Dickscheid, T. (2021). Contrastive Representation Learning For Whole Brain Cytoarchitectonic Mapping In Histological Human Brain Sections. 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 603–606. https://doi.org/10.1109/ISBI48211.2021.9433986
  • Schiffer, C., Harmeling, S., Amunts, K., & Dickscheid, T. (2021). 2D Histology Meets 3D Topology: Cytoarchitectonic Brain Mapping with Graph Neural Networks. In M. de Bruijne, P. C. Cattin, S. Cotin, N. Padoy, S. Speidel, Y. Zheng, & C. Essert (Eds), Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 (pp. 395–404). Springer International Publishing. https://doi.org/10.1007/978-3-030-87237-3_38
  • Schiffer, C., Schuhmacher, L., Amunts, K., & Dickscheid, T. (2021). Learning to predict cutting angles from histological human brain sections.
  • Schiffer, C., Spitzer, H., Kiwitz, K., Unger, N., Wagstyl, K., Evans, A. C., Harmeling, S., Amunts, K., & Dickscheid, T. (2021). Convolutional neural networks for cytoarchitectonic brain mapping at large scale. NeuroImage, 240, 118327. https://doi.org/10.1016/j.neuroimage.2021.118327

2020

  • Kiwitz, K., Schiffer, C., Spitzer, H., Dickscheid, T., & Amunts, K. (2020). Deep learning networks reflect cytoarchitectonic features used in brain mapping. Scientific Reports, 10(1), Article 1. https://doi.org/10.1038/s41598-020-78638-y
  • Wagstyl, K., Larocque, S., Cucurull, G., Lepage, C., Cohen, J. P., Bludau, S., Palomero-Gallagher, N., Lewis, L. B., Funck, T., Spitzer, H., Dickscheid, T., Fletcher, P. C., Romero, A., Zilles, K., Amunts, K., Bengio, Y., & Evans, A. C. (2020). BigBrain 3D atlas of cortical layers: Cortical and laminar thickness gradients diverge in sensory and motor cortices. PLoS Biology, 18(4), e3000678. https://doi.org/10.1371/journal.pbio.3000678

2019

  • Dickscheid, T., Haas, S., Bludau, S., Glock, P., Huysegoms, M., & Amunts, K. (2019). Towards 3D Reconstruction of Neuronal Cell Distributions from Histological Human Brain Sections. Future Trends of HPC in a Disruptive Scenario, 223–239. https://doi.org/10.3233/APC190016
  • Huysegoms, M., Haas, S., Bludau, S., Amunts, K., & Dickscheid, T. (2019). Aligning Images of Large Human Brain Sections on a Cellular Level using Bisected Cells. 25th Annual Meeting of the Organization for Human Brain Mapping (OHBM).
  • Oden, L., Schiffer, C., Spitzer, H., Dickscheid, T., & Pleiter, D. (2019). IO Challenges for Human Brain Atlasing Using Deep Learning Methods—An In-Depth Analysis. 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 291–298. https://doi.org/10.1109/EMPDP.2019.8671630
  • Schiffer, C., Spitzer, H., Kiwitz, K., Amunts, K., & Dickscheid, T. (2019). Deep Learning speeds up gapless cytoarchitectonic mapping in serial histological sections. 25th Annual Meeting of the Organization for Human Brain Mapping (OHBM).

2018

  • Lebenberg, J., Labit, M., Auzias, G., Mohlberg, H., Fischer, C., Rivière, D., Duchesnay, E., Kabdebon, C., Leroy, F., Labra, N., Poupon, F., Dickscheid, T., Hertz-Pannier, L., Poupon, C., Dehaene-Lambertz, G., Hüppi, P., Amunts, K., Dubois, J., & Mangin, J.-F. (2018). A framework based on sulcal constraints to align preterm, infant and adult human brain images acquired in vivo and post mortem. Brain Structure and Function, 223(9), 4153–4168. https://doi.org/10.1007/s00429-018-1735-9
  • Spitzer, H., Amunts, K., Harmeling, S., & Dickscheid, T. (2018). Compact feature representations for human brain cytoarchitecture using self-supervised learning. International Conference on Medical Imaging with Deep Learning.
  • Spitzer, H., Kiwitz, K., Amunts, K., Harmeling, S., & Dickscheid, T. (2018). Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks. In A. F. Frangi, J. A. Schnabel, C. Davatzikos, C. Alberola-López, & G. Fichtinger (Eds), Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 (pp. 663–671). Springer International Publishing.

2017

  • Spitzer, H., Amunts, K., & Dickscheid, T. (2017). Application of Deep Learning for Human Visual Cortex Parcellation in Histological Sections. 23th Annual Meeting of the Organization for Human Brain Mapping (OHBM).
  • Spitzer, H., Amunts, K., Harmeling, S., & Dickscheid, T. (2017). Parcellation of visual cortex on high-resolution histological brain sections using convolutional neural networks. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 920–923. https://doi.org/10.1109/ISBI.2017.7950666

2016

  • Bludau, S., Dickscheid, T., Iannilli, F., & Amunts, K. (2016, June). 3D reconstruction of cell distributions in the human subthalamic nucleus at 1 micron resolution. 22nd Annual Meeting of the Organization for Human Brain Mapping (OHBM).
  • Mangin, J.-F., Lebenberg, J., Lefranc, S., Labra, N., Auzias, G., Labit, M., Guevara, M. A., Mohlberg, H., Roca, P., Guevara, P., Dubois, J., Leroy, F., Dehaene-Lambertz, G., Cachia, A., Dickscheid, T., Coulon, O., Poupon, C., Rivière, D., Amunts, K., & Sun, Z. Y. (2016). Spatial normalization of brain images and beyond. Medical Image Analysis, 33, 127–133. https://doi.org/10.1016/j.media.2016.06.008
  • Schober, M., Axer, M., Huysegoms, M., Schubert, N., Amunts, K., & Dickscheid, T. (2016). Morphing Image Masks for Stacked Histological Sections Using Laplace’s Equation. In T. Tolxdorff, T. M. Deserno, H. Handels, & H.-P. Meinzer (Eds), Bildverarbeitung für die Medizin 2016 (pp. 146–151). Springer Berlin Heidelberg.
  • Spitzer, H., Stibane, D., Caspers, S., Zilles, K., Amunts, K., & Dickscheid, T. (2016, June). Feasibility of deep learning for automatic parcellation of cortical regions in histological sections. 22nd Annual Meeting of the Organization for Human Brain Mapping (OHBM).

2013

  • Amunts, K., Lepage, C., Borgeat, L., Mohlberg, H., Dickscheid, T., Rousseau, M.-E., Bludau, S., Bazin, P.-L., Lewis, L. B., Oros-Peusquens, A.-M., Shah, N. J., Lippert, T., Zilles, K., & Evans, A. C. (2013). BigBrain: An Ultrahigh-Resolution 3D Human Brain Model. Science, 340(6139), 1472–1475. https://doi.org/10.1126/science.1235381
  • Dickscheid, T., & Förstner, W. (2013). A Trainable Markov Random Field for Low-Level Image Feature Matching with Spatial Relationships. Photogrammetrie - Fernerkundung - Geoinformation, 2013(4), 269–283. https://doi.org/10.1127/1432-8364/2013/0176
  • Pieperhoff, P., Dickscheid, T., & Amunts, K. (2013). Grundlagen der Morphometrie. In F. Schneider & G. R. Fink (Eds), Funktionelle MRT in Psychiatrie und Neurologie (pp. 87–101). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-29800-4_5

2012

  • Dammers, J., Breuer, L., Axer, M., Kleiner, M., Eiben, B., Gräßel, D., Dickscheid, T., Zilles, K., Amunts, K., Shah, N. J., & Pietrzyk, U. (2012). Automatic identification of gray and white matter components in polarized light imaging. NeuroImage, 59(2), 1338–1347. https://doi.org/10.1016/j.neuroimage.2011.08.030
  • Kleiner, M., Axer, M., Gräßel, D., Reckfort, J., Pietrzyk, U., Amunts, K., & Dickscheid, T. (2012). Classification of Ambiguous Nerve Fiber Orientations in 3D Polarized Light Imaging. In N. Ayache, H. Delingette, P. Golland, & K. Mori (Eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012 (pp. 206–213). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-33415-3_26

2011

  • Axer, M., Grässel, D., Kleiner, M., Dammers, J., Dickscheid, T., Reckfort, J., Hütz, T., Eiben, B., Pietrzyk, U., Zilles, K., & Amunts, K. (2011). High-Resolution Fiber Tract Reconstruction in the Human Brain by Means of Three-Dimensional Polarized Light Imaging. Frontiers in Neuroinformatics, 5. https://doi.org/10.3389/fninf.2011.00034
  • Dickscheid, T., Schindler, F., & Förstner, W. (2011). Coding Images with Local Features. International Journal of Computer Vision, 94(2), 154–174. https://doi.org/10.1007/s11263-010-0340-z

2009

  • Dickscheid, T., & Förstner, W. (2009). Evaluating the Suitability of Feature Detectors for Automatic Image Orientation Systems. In M. Fritz, B. Schiele, & J. H. Piater (Eds), Computer Vision Systems (pp. 305–314). Springer Berlin Heidelberg.
  • Förstner, W., Dickscheid, T., & Schindler, F. (2009a). Detecting interpretable and accurate scale-invariant keypoints. 2009 IEEE 12th International Conference on Computer Vision, 2256–2263. https://doi.org/10.1109/ICCV.2009.5459458
  • Förstner, W., Dickscheid, T., & Schindler, F. (2009b). On the completeness of coding with image features. Procedings of the British Machine Vision Conference 2009. https://doi.org/10.5244/c.23.1

2008

2005

  • Paulus, D., Dickscheid, T., & Berg, K. . (2005). Design of AN IMage AnaLysis system. Seventh International Workshop on Computer Architecture for Machine Perception (CAMP’05), 147–152. https://doi.org/10.1109/CAMP.2005.20
  • Schmidt, C., Tavernier, L., Dickscheid, T., & Paulus, D. (2005). Computer Analysis of Ornaments. In V. Cappellini & J. Hemsley (Eds), Electronic Imaging & the Visual Arts (pp. 129–134). Pitagora Editrice Bologna.