Difference between revisions of "Main Page/SlicerCommunity"

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* [[Main_Page/SlicerCommunity-2005-2010|2010-2005]]
 
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We invite you to provide information on how you are using 3D Slicer to produce peer-reviewed research. Information about the scientific impact of this tool is helpful in raising funding for the continued support.
 
We invite you to provide information on how you are using 3D Slicer to produce peer-reviewed research. Information about the scientific impact of this tool is helpful in raising funding for the continued support.

Revision as of 18:09, 12 October 2018

Home < Main Page < SlicerCommunity

3D Slicer Enabled Research

3D Slicer is a free open source software package distributed under a BSD style license.

The majority of funding for the development of 3D slicer comes from a number of grants and contracts from the National Institutes of Health. See Slicer Acknowledgments for more information.

Since 1999, with support from the NIH and a worldwide open source developer community, we have developed, distributed, and supported 3D Slicer, a free and powerful software platform for analysis, integration, and visualization of medical images that allows even those with limited image processing experience to effectively explore and quantify their imaging data for hypothesis-driven research.

A trajectory of steadily increasing rates for downloads (425,000+ in the past seven years, of which 113,398 were in the last year alone), more than 7,300 citations on Google Scholar, and an open source hackathon series continuously running since 2005, are indicators of the large and active community that relies on 3D Slicer.

Since the inception of the NCI QIN and ITCR networks, the use of 3D Slicer for quantitative cancer image analysis research has grown substantially. More than half of the 3D Slicer citations on Google Scholar use it for cancer research. The research spans cancers of the prostate (876), brain (2,180), lung (1,210), and breast (975), and involves multimodality imaging based staging and characterization, correlation with histopathology, segmentation of tumor and critical structures for precision biopsy, surgery, and radiation therapy, and quantitative assessment of response to therapy.

The following pages are a sample of the research done using 3D Slicer by the community:

We invite you to provide information on how you are using 3D Slicer to produce peer-reviewed research. Information about the scientific impact of this tool is helpful in raising funding for the continued support.