ZFIN ID: ZDB-PUB-171025-8
A novel non-rigid registration algorithm for zebrafish larval images
Ghosal, S., Banerjee, S., Tiso, N., Grisan, E., Chowdhury, A.S.
Date: 2017
Source: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference   2017: 321-324 (Journal)
Registered Authors: Tiso, Natascia
Keywords: none
MeSH Terms:
  • Algorithms*
  • Animals
  • Brain
  • Imaging, Three-Dimensional
  • Larva
  • Software
  • Zebrafish
PubMed: 29059875 Full text @ Conf. Proc. IEEE Eng. Med. Biol. Soc.
Precise three-dimensional mapping of a large number of gene expression patterns, neuronal types and connections to an anatomical reference helps us to understand the vertebrate brain and its development. Zebrafish has evolved as a model organism for such study. In this paper, we propose a novel non-rigid registration algorithm for volumetric zebrafish larval image datasets. A coarse affine registration using the L-BFGS algorithm is applied first on the moving dataset. We then divide this coarsely registered moving image and the reference image into a union of overlapping patches. Minimum weight bipartite graph matching algorithm is employed to find the correspondence between the two sets of patches. The corresponding patches are then registered using the diffeomorphic demons method with proper intra-patch regularization. For each voxel lying in the overlapping regions, we impose inter-patch regularization through a composite transformation obtained from the adjacent transformation fields. Experimental results on four multi-view confocal 3D datasets show the advantage of the proposed solution over the existing ViBE-Z software.