Kitware has been awarded $181,700 in sub-recipient funding on a grant from the U.S. National Center of Research Resources, part of the National Institutes of Health (NIH). The funding will be used to make enhancements to 3D Slicer, an open-source platform for medical image segmentation, registration, visualization, and analysis. 3D Slicer is funded by grants associated with the National Alliance for Medical Image Computing (NA-MIC) and the Neuroimaging Analysis Center (NAC), and supported by extensive user and developer communities.
Dr. Stephen Aylward, Director of Medical Imaging at Kitware, will act as Principle Investigator and Julien Finet will act as the lead architect and developer on this project. They will lead the collaboration between Kitware and the NIH-NCRR, Slicer, NA-MIC, and NAC communities to extend Slicer in three critical ways: with a simplified user interface, the implementation of fully-automated user interface testing, and the addition of SimpleITK access through Python.
The development of a simplified user interface will reduce the amount of training required for the most common tasks in Slicer. This effort will minimize the learning curve for end-users; simplify the development of extensions to the user interface for new algorithms; facilitate more frequent use of Slicer; and address time-consuming components to allow for more training time on advanced topics.
The creation of an automated user interface testing system will be achieved by adopting the GUI testing environment developed for ParaView. The testing will be run nightly using Kitware’s CTest and CDash regression testing and reporting systems. The nightly feedback will keep developers more informed about the overall quality of their software and the impact of their changes to the code. Additionally, the extensive collection of training material for Slicer will be automated as GUI tests. Those automated interactions with Slicer will be used for online courses and demonstrations.
This funding will also enable Kitware to integrate Slicer with SimpleITK, a simplified protocol language interface built on top of ITK to facilitate rapid prototyping, education, and interpreted languages. This enhancement will make 3D Slicer’s Python interface a fully-functional, script-based image analysis and display toolkit that provides access to VTK’s visualization API and the Qt GUI API.
“These enhancements will create considerable opportunities for new and existing users of 3D Slicer by extending the tool’s capabilities,” said Dr. Stephen Aylward. “We are looking forward to seeing the impact of these enhancements on the stability, usability, and utility of the Slicer platform and on the broader adoption of Slicer by the medical community.”