no code implementations • 27 Feb 2024 • Alexander Oberstrass, Jordan DeKraker, Nicola Palomero-Gallagher, Sascha E. A. Muenzing, Alan C. Evans, Markus Axer, Katrin Amunts, Timo Dickscheid
Understanding the cortical organization of the human brain requires interpretable descriptors for distinct structural and functional imaging data.
no code implementations • 30 Jan 2024 • Alexander Oberstrass, Sascha E. A. Muenzing, Meiqi Niu, Nicola Palomero-Gallagher, Christian Schiffer, Markus Axer, Katrin Amunts, Timo Dickscheid
To this end, we propose the application of a fully data-driven approach to characterize nerve fiber architecture in 3D-PLI images using self-supervised representation learning.
no code implementations • 28 Nov 2023 • Jan-Oliver Kropp, Christian Schiffer, Katrin Amunts, Timo Dickscheid
This is the basis to study the multi-scale architecture of the brain regarding its subdivision into brain areas and nuclei, cortical layers, columns, and cell clusters down to single cell morphology Methods for brain mapping and cell segmentation exploit such images to enable rapid and automated analysis of cytoarchitecture and cell distribution in complete series of histological sections.
no code implementations • 10 Aug 2023 • Jun Ma, Ronald Xie, Shamini Ayyadhury, Cheng Ge, Anubha Gupta, Ritu Gupta, Song Gu, Yao Zhang, Gihun Lee, Joonkee Kim, Wei Lou, Haofeng Li, Eric Upschulte, Timo Dickscheid, José Guilherme de Almeida, Yixin Wang, Lin Han, Xin Yang, Marco Labagnara, Vojislav Gligorovski, Maxime Scheder, Sahand Jamal Rahi, Carly Kempster, Alice Pollitt, Leon Espinosa, Tâm Mignot, Jan Moritz Middeke, Jan-Niklas Eckardt, Wangkai Li, Zhaoyang Li, Xiaochen Cai, Bizhe Bai, Noah F. Greenwald, David Van Valen, Erin Weisbart, Beth A. Cimini, Trevor Cheung, Oscar Brück, Gary D. Bader, Bo wang
This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging.
1 code implementation • NeurIPS CellSeg 2022 2022 • Eric Upschulte, Stefan Harmeling, Katrin Amunts, Timo Dickscheid
In the context of the NeurIPS 22 Cell Segmentation Challenge, the proposed solution is shown to generalize well in a multi-modality setting, while respecting domain-specific requirements such as focusing on specific cell types.
no code implementations • 12 Apr 2022 • Esteban Vaca, Miriam Menzel, Katrin Amunts, Markus Axer, Timo Dickscheid
Scattered Light Imaging (SLI) is a novel approach for microscopically revealing the fibre architecture of unstained brain sections.
2 code implementations • 7 Apr 2021 • Eric Upschulte, Stefan Harmeling, Katrin Amunts, Timo Dickscheid
We construct CPN models with different backbone networks, and apply them to instance segmentation of cells in datasets from different modalities.
no code implementations • 9 Mar 2021 • Christian Schiffer, Stefan Harmeling, Katrin Amunts, Timo Dickscheid
By solving the brain mapping problem on this graph using graph neural networks, we obtain significantly improved classification results.
1 code implementation • 11 Feb 2021 • Michael Schirner, Lia Domide, Dionysios Perdikis, Paul Triebkorn, Leon Stefanovski, Roopa Pai, Paula Popa, Bogdan Valean, Jessica Palmer, Chloê Langford, André Blickensdörfer, Michiel van der Vlag, Sandra Diaz-Pier, Alexander Peyser, Wouter Klijn, Dirk Pleiter, Anne Nahm, Oliver Schmid, Marmaduke Woodman, Lyuba Zehl, Jan Fousek, Spase Petkoski, Lionel Kusch, Meysam Hashemi, Daniele Marinazzo, Jean-François Mangin, Agnes Flöel, Simisola Akintoye, Bernd Carsten Stahl, Michael Cepic, Emily Johnson, Anthony R. McIntosh, Claus C. Hilgetag, Marc Morgan, Bernd Schuller, Alex Upton, Colin McMurtrie, Timo Dickscheid, Jan G. Bjaalie, Katrin Amunts, Jochen Mersmann, Viktor Jirsa, Petra Ritter
The Virtual Brain (TVB) is now available as open-source cloud ecosystem on EBRAINS, a shared digital research platform for brain science.
Bayesian Inference Code Generation Computational Engineering, Finance, and Science Cryptography and Security Distributed, Parallel, and Cluster Computing Neurons and Cognition Quantitative Methods
no code implementations • 25 Nov 2020 • Christian Schiffer, Hannah Spitzer, Kai Kiwitz, Nina Unger, Konrad Wagstyl, Alan C. Evans, Stefan Harmeling, Katrin Amunts, Timo Dickscheid
Here we present a new workflow for mapping cytoarchitectonic areas in large series of cell-body stained histological sections of human postmortem brains.
no code implementations • 25 Nov 2020 • Christian Schiffer, Katrin Amunts, Stefan Harmeling, Timo Dickscheid
Cytoarchitectonic maps provide microstructural reference parcellations of the brain, describing its organization in terms of the spatial arrangement of neuronal cell bodies as measured from histological tissue sections.
no code implementations • 13 Jun 2018 • Hannah Spitzer, Kai Kiwitz, Katrin Amunts, Stefan Harmeling, Timo Dickscheid
We show that the self-supervised model has implicitly learned to distinguish several cortical brain areas -- a strong indicator that the proposed auxiliary task is appropriate for cytoarchitectonic mapping.
no code implementations • 30 May 2017 • Hannah Spitzer, Katrin Amunts, Stefan Harmeling, Timo Dickscheid
Its high resolution allows the study of laminar and columnar patterns of cell distributions, which build an important basis for the simulation of cortical areas and networks.