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A Large Deformation Diffeomorphic Approach to Registration of CLARITY Images via Mutual Information

  • Kwame S. KuttenEmail author
  • Nicolas Charon
  • Michael I. Miller
  • J. Tilak Ratnanather
  • Jordan Matelsky
  • Alexander D. Baden
  • Kunal Lillaney
  • Karl Deisseroth
  • Li Ye
  • Joshua T. Vogelstein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10433)

Abstract

CLARITY is a method for converting biological tissues into translucent and porous hydrogel-tissue hybrids. This facilitates interrogation with light sheet microscopy and penetration of molecular probes while avoiding physical slicing. In this work, we develop a pipeline for registering CLARIfied mouse brains to an annotated brain atlas. Due to the novelty of this microscopy technique it is impractical to use absolute intensity values to align these images to existing standard atlases. Thus we adopt a large deformation diffeomorphic approach for registering images via mutual information matching. Furthermore we show how a cascaded multi-resolution approach can improve registration quality while reducing algorithm run time. As acquired image volumes were over a terabyte in size, they were far too large for work on personal computers. Therefore the NeuroData computational infrastructure was deployed for multi-resolution storage and visualization of these images and aligned annotations on the web.

Notes

Acknowledgments

The authors are grateful for support from the DARPA SIMPLEX program through SPAWAR contract N66001-15-C-4041, DARPA GRAPHS N66001-14-1-4028.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Kwame S. Kutten
    • 1
    Email author
  • Nicolas Charon
    • 1
  • Michael I. Miller
    • 1
  • J. Tilak Ratnanather
    • 1
  • Jordan Matelsky
    • 1
  • Alexander D. Baden
    • 1
  • Kunal Lillaney
    • 1
  • Karl Deisseroth
    • 2
  • Li Ye
    • 2
  • Joshua T. Vogelstein
    • 1
  1. 1.Johns Hopkins UniversityBaltimoreUSA
  2. 2.Stanford UniversityStanfordUSA

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