Difference between revisions of "Main Page/SlicerCommunity"

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The following is a sample of the research performed by the 3D Slicer community:
 
The following is a sample of the research performed by the 3D Slicer community:
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* [[Main_Page/SlicerCommunity-2018|2018]]
 
* [[Main_Page/SlicerCommunity-2018|2018]]
 
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We invite you to provide information using our [https://discourse.slicer.org/ discussion forum] 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 using our [https://discourse.slicer.org/ discussion forum] 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.
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Revision as of 14:34, 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.

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 113,000+ 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 (1000+), brain (2,320+), lung (1,310+), and breast (1010+), 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 is a sample of the research performed by the 3D Slicer community:

We invite you to provide information using our discussion forum 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.