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NLM: Imaging Methods Assessment and Reporting (Size: 13Gb)

Imaging Methods Assessment and Reporting (IMAR)

The goal of the NLM's IMAR program is to provide data, methods, and computational resources for the quantitative comparison of image segmentation, registration, and computer-aided diagnosis methods.

This project is lead by Dr. Terry Yoo at the NLM and hosted by Kitware. The project builds upon Kitware's MIDAS technology: a collection of server/client tools for image and data assimilation. More information on MIDAS is available on the product page

Three types of experimental designs are supported for method evaluation. They are as follows:

1. Blinded Algorithm Evaluation
   Algorithm evaluators apply for access to evaluation data and upload their results. Results are automatically compared with sequested truth.
   • The Retrospective Image Registration Evaluation Project (RIRE) v2.0
     
     
2. Public Data Standards
   Algorithm evaluators are encouraged to download the data from these sites when conduction their own evaluations.
   • NLM's Public Data MIDAS Community
     • Zebrafish data
     • Liver tumor data with truth
       
     • 100 Healthy MRI and MRA
   • The BrainWeb project
   • NA-MIC's Public Data and Slicer Tutorial Data
     

Algorithm evaluators are encouraged to submit open-source implimentations and summaries of their results to the open-access Insight Journal.

New evaluation datasets and experiments are welcome. Please contact Dr. Terry Yoo or Dr. Stephen Aylward to arrange a submission.

Please use this identifier to cite or link to this community: http://hdl.handle.net/1926/193