AUTHOR=Avants Brian B. , Tustison Nicholas J. , Stauffer Michael , Song Gang , Wu Baohua , Gee James C. 

TITLE=The Insight ToolKit image registration framework

JOURNAL=Frontiers in Neuroinformatics

VOLUME=Volume 8 - 2014

YEAR=2014

URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2014.00044

DOI=10.3389/fninf.2014.00044

ISSN=1662-5196

ABSTRACT=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 several<br/>advances 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.<br/>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 to<br/>more 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 brain<br/>labeling.