@inproceedings{5db28c9b105b4dfb8249861d1ea649ed,
title = "GORDA: Graph-Based Orientation Distribution Analysis of SLI Scatterometry Patterns of Nerve Fibres",
abstract = "Scattered Light Imaging (SLI) is a novel approach for microscopically revealing the fibre architecture of unstained brain sections. The measurements are obtained by illuminating brain sections from different angles and measuring the transmitted (scattered) light under normal incidence. The evaluation of scattering profiles commonly relies on a peak picking technique and feature extraction from the peaks, which allows quantitative determination of parallel and crossing in-plane nerve fibre directions for each image pixel. However, the estimation of the 3D orientation of the fibres cannot be assessed with the traditional methodology. We propose an unsupervised learning approach using spherical convolutions for estimating the 3D orientation of neural fibres, resulting in a more detailed interpretation of the fibre orientation distributions in the brain.",
keywords = "CNNs, Fibre Architecture, Human Brain, Spherical Convolution, Unsupervised Learning",
author = "Esteban Vaca and Miriam Menzel and Katrin Amunts and Markus Axer and Timo Dickscheid",
year = "2022",
doi = "10.1109/ISBI52829.2022.9761492",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE",
booktitle = "ISBI 2022 - Proceedings",
address = "United States",
note = "19th IEEE International Symposium on Biomedical Imaging, ISBI 2022 ; Conference date: 28-03-2022 Through 31-03-2022",
}