A6 - Learning to predict cutting angles from histological human brain sections

Christian Schiffer, Luisa Schuhmacher, Katrin Amunts, Timo Dickscheid

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Studying brain architecture at the cellular level requires histological image analysis of sectioned postmortem samples. We trained a deep neural network to estimate relative angles between the cutting plane and the local 3D brain surface from 2D cortical image patches sampled from microscopic scans of human brain tissue sections. The model allows to automatically identify obliquely cut tissue parts, which often confuse downstream texture classification tasks and typically require specific treatment in image analysis workflows. It has immediate applications for the automated analysis of brain structures, like cytoarchitectonic mapping of the highly convoluted human brain.
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Wednesday 7th July
A4-12 (short): Segmentation - 13:45 - 14:30 (UTC+2)
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