Slicer and The Cancer Imaging Archive: Towards the shared goal of making the most of medical imaging resources
By providing open access to DICOM images, associated metadata and related resources, the The Cancer Imaging Archive (TCIA) opens the way to leveraging the use of medical imaging data in cancer research.
3D analysis and visualization
The Slicer software platform pursues the shared goal of making the most of medical imaging by assisting the extraction of meaningful information from patient data.
Slicer is a software platform for medical image processing and 3D visualization of patient data. This research tool provides a simple and practical solution for assisting the extraction of meaningful information from medical images, and presenting them in three-dimensional reconstructions of the anatomy of the patient. Slicer combines basic and advanced image analysis functionalities: from visualizing and interacting in 3D with patient datasets to extracting key structures or quantifying lesions changes in longitudinal studies.
A research platform
By providing a common open-source platform where clinicians and scientists can interact, Slicer fosters the development of innovative solutions for the multidisciplinary challenges posed by cancer imaging. Slicer offers a great flexibility to both users and developers: the software can read all common types of imaging data, such as MRI, CT, Ultrasound and Microscopy images, supports most existing file formats, such as DICOM, and works on Windows, Mac and Linux computers.
TCIA now serves as an extension to this research platform by providing large quantities of high quality cancer imaging data to work with in Slicer. Below is a list of key URLs which Slicer users may find useful:
- Summary of available data in TCIA
- TCIA Account Registration
- Publications leveraging TCIA data
- TCIA Citation Guidelines
Transferring key technologies from scientists to clinicians
Along with the development of the software platform, a strong commitment to training and education has been made so as to accelerate the transfer of advanced medical image analysis techniques to the clinicians for whom they were developed. A compendium of image analysis courses is freely available to scientific community for self-teaching, and tailored workshops with instructor-guided hands-on sessions provide clinicians and scientists the ability to become autonomous with the software in a minimum amount of time. An example of such training event is the Slicer Training workshop at the National Cancer Institute.
Slicer3 is the result of a multi-institutions effort on a national scale for developing, delivering and teaching technologies that can help clinicians tackling the many challenges of cancer imaging. This research tool is supported by the National Institutes of Health, and is made freely available to the clinical and scientific community.