Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks

Understand

Cytoarchitectonic parcellations of the human brain serve as anatomical references in multimodal atlas frameworks.

• They are based on analysis of cell-body stained histological sections and the identification of borders between brain areas.
• The de-facto standard involves a semi-automatic, reproducible border detection, but does not scale with high-throughput imaging in large series of sections at microscopical resolution.
• Automatic parcellation, however, is extremely challenging due to high variation in the data, and the need for a large field of view at microscopic resolution.