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An ImageJ-based tool for three-dimensional registration between different types of microscopic images.

Hiroshi KoyamaKanae KishiSeiya MikoshibaToshihiko Fujimori
Published in: Development, growth & differentiation (2022)
Three-dimensional (3D) registration (i.e. alignment) between two microscopic images is substantially helpful to study tissues not adhere to substrates such as mouse embryos and organoids which are often 3-dimensionally rotated during imaging. However, there is no 3D registration tool easily accessible for experimental biologists. Here we developed an ImageJ-based tool which achieves 3D registration accompanying both quantitative evaluation of the accuracy and reconstruction of 3D rotated images. In this tool, several landmarks are manually provided in two images to be aligned, and 3D rotation is computed so that the distances between the paired landmarks from the two images are minimized. By simultaneously providing multiple points (e.g. all nuclei in the regions of interest) other than the landmarks in the two images, the correspondence of each point between the two images is quantitatively explored: a certain nucleus in one image corresponds to which nucleus in another image. Furthermore, the 3D rotation is applied to one of the two images, resulting in reconstruction of 3D rotated images. We demonstrated that this tool successfully achieved 3D registration and reconstruction of images in mouse pre- and post-implantation embryos, where one image was obtained during live imaging and another image from fixed embryos after live imaging. This approach provides a versatile tool applicable for various tissues and species. This article is protected by copyright. All rights reserved.
Keyphrases
  • deep learning
  • convolutional neural network
  • optical coherence tomography
  • high resolution
  • gene expression
  • machine learning
  • magnetic resonance imaging
  • magnetic resonance
  • photodynamic therapy