The Insight Toolkit was developed by six principal organizations, three commercial (Kitware, GE Corporate R&D, and Insightful) and three academic (UNC Chapel Hill, University of Utah, and University of Pennsylvania). Additional team members include Harvard Brigham & Women's Hospital, University of Pittsburgh, and Columbia University. The funding for the project is from the National Library of Medicine at the National Institutes of Health.

Many generous sponsors have supported ITK and the NLM continues to provide executive leadership in the project's administration. ITK has been funded in whole or in part with Federal funds from the National Institutes of Health (NLM, NIDCR, NIMH, NEI, NINDS, NIDCD, NCI), the NSF, and the DoD (TATRC) under the direction of the National Library of Medicine, National Institutes of Health, contracts number N01-LM-9-3531, N01-LM-9-3532, N01-LM-0-3501, N01-LM-0-3502, N01-LM-0-3503, and N01-LM-0-3504.

NLM logo National Library of Medicine (NLM)
NIDCR logo National Institute of Dental and Craniofacial Research (NIDCR)
NSF logo National Science Foundation (NSF)
NEI logo National Eye Institute (NEI)
NINDS logo National Institute of Neurological Disorders and Stroke (NINDS)
NEI logo National Institute of Mental Health (NIMH)
NIDCD logo National Institute on Deafness and Other Communication Disorders (NIDCD)
NCI logo National Cancer Institute (NCI)

The best way to determine the names of developers is to view the CVS source code repository logs. Most of the early developers are listed in the following, however, many developers beyond those listed here will participate in the development of ITK as the code grows and becomes publicly accessible.

Some of the early developers include:
  • Elsa Angelini - Columbia, segmentation algorithms
  • Brian Avants - UPenn; FEM classes, registration algorithms
  • Stephen Aylward - UNC; architecture, algorithms
  • Dan Blezek - GE CRD; testing infrastructure
  • Josh Cates - Utah; imaging and segmentation classes and filters
  • Ting Chen - UPenn, segmentation algorithms
  • Jeffrey Duda - UPenn; FEM classes, registration algorithms
  • James Gee - UPenn; FEM architecture, registration algorithms
  • Bill Hoffman - Kitware; CMake (build process); vxl/vnl numerics; infrastructure (smart pointers, object factories, callback mechanism)
  • Paul Hughett - UPenn; quality, algorithms
  • Luis Ibáñez - UNC (now Kitware); imaging classes and filters
  • Celina Imielinska - Columbia, segmentation algorithms
  • Yinpeng Jin - Columbia, segmentation algorithms
  • Brad King - Kitware; Mesh class, autowrapping of C++ code
  • Bill Lorensen - GE CRD; testing, requirements, architecture
  • Ken Martin - Kitware; Build process, architecture, infrastructure
  • Dimitris Metaxas - UPenn, segmentation algorithms
  • Jim Miller - GE CRD; Image classes, iterators, pipeline update mechanism
  • Lydia Ng - MathSoft (now Insightful); Image filters, clustering/segmentation algorithms
  • Aljaz Noe - UPenn; FEM classes
  • Sayan Pathak – MathSoft (now Insightful); image clustering/segmentation algorithms
  • Will Schroeder - Kitware; architecture, Mesh classes, documentation, algorithms, core classes
  • Marcelo Siqueira - UPenn; FEM classes
  • George Stetton - Pittsburgh; image filters, algorithms
  • Tessa Sundaram - UPenn; FEM classes, registration algorithms
  • Jayaram Udupa - Upenn, segmentation algorithms
  • Ross Whitaker - Utah; architecture, algorithms
  • Ying Zhuge - UPenn, segmentation algorithms