NLM: Imaging Methods Assessment and Reporting |
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http://hdl.handle.net/1926/398 |
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 HERE
Three types of experimental designs are supported for method evaluation. They are as follows:
- Blinded Algorithm Evaluation
Algorithm evaluators apply for access to evaluation data and upload their results. Results are automatically compared with sequested truth. - Automated Evaluation
Algorithm evaluators submit an executable to the website, and it is used to process sequestered data. - 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
New evaluation datasets and experiments are welcome. Please contact Dr. Terry Yoo or Dr. Stephen Aylward to arrange a submission.
Sub-communities within this community
> Automated Evaluation Data> Public Data Standards
> Retrospective Image Registration Evaluation (RIRE)
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