Thousands of medical researchers around the world use VTK -the Visualization Toolkit- an open-source, freely available software development toolkit providing advanced 3D interactive visualization, image processing and analytics algorithms. They either use VTK directly in their in-house research applications or indirectly via one of the multitude of medical image analysis and bioinformatics applications that is built using VTK: Osirix, 3D Slicer, BioImageXD, MedINRIA, VR-Render, GIMIAS, SCIRun, VolView, IGSTK, and others. Furthermore, VTK also provides 3D visualizations for clinical applications such as BrainLAB's Vector Vision surgical guidance system. VTK has been downloaded many hundreds of thousands of times since its initial release in 1993. Considering its broad distribution and prevalent use, it can be argued that VTK has had a greater impact on medical research, and patient care, than any other open-source visualization package. This proposal is in response to the crescendo of requests we have been receiving from the VTK medical community.
The aims are as follows: 1. Update the VTK graphics infrastructure to support efficient representation and rendering of large data, visualizing data over the web and on mobile platforms, and interactively exploring data using 3D widgets. 2. Manage the growth of VTK and its large open-source community by enabling multiple channels whereby code can be easily contributed, discovered, downloaded, and used as modular extensions to VTK. 3. Conduct targeted outreach to maximize the impact of the proposed VTK enhancements on the medical community. We will work collaboratively with five world-leading research labs throughout the proposed process, including the Virtual Lung Project at The University of North Carolina at Chapel Hill, the Institute for Computational Medicine at Johns Hopkins University, and three other labs.

Public Health Relevance

The Visualization Toolkit (VTK) is an open-source, freely available software library for the interactive display and processing of medical images. It is being used in nearly every major medical imaging research application, e.g., Slicer and Osirix, and in several commercial medical applications, e.g., BrainLAB's VectorVision surgical guidance system. VTK development began in 1993 and since then a massive community of users and developers has grown around it. However, VTK needs to be updated to run on mobile platforms, provide web based visualizations, and better handle larger medical data. With those updates, researchers will have new avenues for distributing their work to other researchers and to clinicians, and new medical applications will be inspired.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB014955-01A1
Application #
8505967
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Pai, Vinay Manjunath
Project Start
2013-05-01
Project End
2017-04-30
Budget Start
2013-05-01
Budget End
2014-04-30
Support Year
1
Fiscal Year
2013
Total Cost
$644,139
Indirect Cost
$237,098
Name
Kitware, Inc.
Department
Type
DUNS #
010926207
City
Clifton Park
State
NY
Country
United States
Zip Code
12065
Black, David; Unger, Michael; Fischer, Nele et al. (2018) Auditory display as feedback for a novel eye-tracking system for sterile operating room interaction. Int J Comput Assist Radiol Surg 13:37-45
Black, David; Hahn, Horst K; Kikinis, Ron et al. (2018) Auditory display for fluorescence-guided open brain tumor surgery. Int J Comput Assist Radiol Surg 13:25-35
Megjhani, Murad; Correa de Sampaio, Pedro; Leigh Carstens, Julienne et al. (2017) Morphologically constrained spectral unmixing by dictionary learning for multiplex fluorescence microscopy. Bioinformatics 33:2182-2190
Barton, Emily A; Lu, Yanbin; Megjhani, Murad et al. (2017) Binge alcohol alters exercise-driven neuroplasticity. Neuroscience 343:165-173
Herz, Christian; Fillion-Robin, Jean-Christophe; Onken, Michael et al. (2017) dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM. Cancer Res 77:e87-e90
Kapur, Tina; Pieper, Steve; Fedorov, Andriy et al. (2016) Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience. Med Image Anal 33:176-180
Megjhani, Murad; Rey-Villamizar, Nicolas; Merouane, Amine et al. (2015) Population-scale three-dimensional reconstruction and quantitative profiling of microglia arbors. Bioinformatics 31:2190-8
Xu, Yan; Qiu, Peng; Roysam, Badrinath (2015) Unsupervised Discovery of Subspace Trends. IEEE Trans Pattern Anal Mach Intell 37:2131-45