Frontiers in Neuroinformatics (Apr 2014)

The Insight ToolKit Image Registration Framework

  • Brian eAvants,
  • Nicholas James Tustison,
  • michael estauffer,
  • Gang eSong,
  • Baohua eWu,
  • James eGee

DOI
https://doi.org/10.3389/fninf.2014.00044
Journal volume & issue
Vol. 8

Abstract

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Publicly available scientific resources help establish evaluation standards, provide a platform for teaching and improve reproducibility. Version 4 of the Insight ToolKit ( ITK4 ) seeks to es- tablish new standards in publicly available image registration methodology. ITK4 makes severaladvances in comparison to previous versions of ITK. ITK4 supports both multivariate images and objective functions; it also unifies high-dimensional (deformation field) and low-dimensional (affine) transformations with metrics that are reusable across transform types and with com- posite transforms that allow arbitrary series of geometric mappings to be chained together seamlessly. Metrics and optimizers take advantage of multi-core resources, when available.Furthermore, ITK4 reduces the parameter optimization burden via principled heuristics that automatically set scaling across disparate parameter types (rotations versus translations). A related approach also constrains steps sizes for gradient-based optimizers. The result is that tuning for different metrics and/or image pairs is rarely necessary allowing the researcher tomore easily focus on design/comparison of registration strategies. In total, the ITK4 contribu- tion is intended as a structure to support reproducible research practices, will provide a more extensive foundation against which to evaluate new work in image registration and also enable application level programmers a broad suite of tools on which to build. Finally, we contextu- alize this work with a reference registration evaluation study with application to pediatric brainlabeling.

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