Open source solving visualization challenges, speed development

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Open source visualization can help radiologists and researchers visualize and analyze the expanding data sets generated by CT, MRI and PET scanners, David E. Avrin, MD, PhD and Society for Imaging Informatics in Medicine (SIIM) open source session chair, told an audience at SIIM yesterday in Austin, Texas.
Leading open source solutions include Insight Segmentation and Registration Toolkit (ITK), Visualization Toolkit (VTK) and ImageJ. The Insight Software Consortium (ISC) is a non-profit resource that educates, promotes and supports open source, medical imaging software, data and publications.

Why open source

Digital acquisition devices, PACS adoption and evidence-based medicine are fueling demand for advanced clinical applications and have led to a tremendous software gap, said Rick Avila, MS, director of medical applications at Kitware, Inc. Radiology requires more efficient software development methods to facilitate advanced image review solutions, yet it can take years to develop software solutions through closed systems.
Open source harnesses the collective experience of algorithm developers and software engineers worldwide to provide a path toward efficient development, reuse and validation of computation architectures and algorithms. The end result is faster, more economical evaluation and deployment of state-of-the-art architectures.

VTK, ITK and ImageJ defined

  • VTK: an object-oriented software system for 3D computer graphics, image processing and visualization.
  • ITK: an object-oriented software toolkit for performing medical image segmentation and registration.
  • ImageJ: a free open source image analysis software that can be applied to segmentation, image conversion, perfusion and diffusion MR analysis and software verification.

Going forward

Developers will turn to open source toolkits to build new specialized toolkits for specific clinical applications. For example, the Image Guided Surgery Toolkit (IGTSK) currently in development will provide a framework for image-guided surgery and intervention.

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