75 citations · 122 across the 6 of their papers we have counts for
6 papers
CytoNet: A Foundation Model for the Human Cerebral Cortex at Cellular Resolution
Christian Schiffer, Zeynep Boztoprak, Jan-Oliver Kropp +7
Studying the cellular architecture of the human cerebral cortex is essential for understanding how the brain is organized from the micro to the macro level, and how it functions. H…
Robust and Generalisable Segmentation of Subtle Epilepsy-causing Lesions: a Graph Convolutional Approach
Hannah Spitzer, Mathilde Ripart, Abdulah Fawaz +6
Focal cortical dysplasia (FCD) is a leading cause of drug-resistant focal epilepsy, which can be cured by surgery. These lesions are extremely subtle and often missed even by exper…
Noise transfer for unsupervised domain adaptation of retinal OCT images
Valentin Koch, Olle Holmberg, Hannah Spitzer +4
Optical coherence tomography (OCT) imaging from different camera devices causes challenging domain shifts and can cause a severe drop in accuracy for machine learning models. In th…
Convolutional Neural Networks for cytoarchitectonic brain mapping at large scale
Christian Schiffer, Hannah Spitzer, Kai Kiwitz +6
Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cytoarchitecture is a basic prin…
Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks
Hannah Spitzer, Kai Kiwitz, Katrin Amunts +2
Cytoarchitectonic parcellations of the human brain serve as anatomical references in multimodal atlas frameworks. They are based on analysis of cell-body stained histological secti…
Parcellation of Visual Cortex on high-resolution histological Brain Sections using Convolutional Neural Networks
Hannah Spitzer, Katrin Amunts, Stefan Harmeling +1
Microscopic analysis of histological sections is considered the "gold standard" to verify structural parcellations in the human brain. Its high resolution allows the study of lamin…