Reconstructing neuronal anatomy from whole-brain images

James Gornet, Kannan Umadevi Venkataraju, Arun Narasimhan, Nicholas Turner, Kisuk Lee, H. Sebastian Seung, Pavel Osten, Uygar Sumbul

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Reconstructing multiple molecularly defined neurons from individual brains and across multiple brain regions can reveal organizational principles of the nervous system. However, high resolution imaging of the whole brain is a technically challenging and slow process. Recently, oblique light sheet microscopy has emerged as a rapid imaging method that can provide whole brain fluorescence microscopy at a voxel size of 0.4\times 0.4\times 2.5\mu \mathrm{m}^{3}. On the other hand, complex image artifacts due to whole-brain coverage produce apparent discontinuities in neuronal arbors. Here, we present connectivity-preserving methods and data augmentation strategies for supervised learning of neuroanatomy from light microscopy using neural networks. We quantify the merit of our approach by implementing an end-to-end automated tracing pipeline. Lastly, we demonstrate a scalable, distributed implementation that can reconstruct the large datasets that sub-micron whole-brain images produce.

Original languageEnglish (US)
Title of host publicationISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
PublisherIEEE Computer Society
Pages218-222
Number of pages5
ISBN (Electronic)9781538636411
DOIs
StatePublished - Apr 2019
Event16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 - Venice, Italy
Duration: Apr 8 2019Apr 11 2019

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2019-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
CountryItaly
CityVenice
Period4/8/194/11/19

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Keywords

  • Image segmentation
  • Light microscopy
  • Machine learning

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  • Cite this

    Gornet, J., Venkataraju, K. U., Narasimhan, A., Turner, N., Lee, K., Seung, H. S., Osten, P., & Sumbul, U. (2019). Reconstructing neuronal anatomy from whole-brain images. In ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging (pp. 218-222). [8759197] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2019-April). IEEE Computer Society. https://doi.org/10.1109/ISBI.2019.8759197