Welcome to Retrospective Image Registration Evaluation Project, Version 2.0!
Update: Datasets are now available as open-access!
The project is designed to compare retrospective CT-MR and PET-MR registration techniques used by a number of groups. It involves the use of a database of image volumes, commonly known as the "Vanderbilt Database", on which the registrations are to be performed. Collaborating groups may download the datasets freely and perform registrations on the image volumes using their own retrospective techniques. It is no longer required to submit the results of the registration to the RIRE website.
The "truth" transforms have been defined using a prospective, marker-based technique, and they remain sequestered. New to Version 2.0, collaborating groups may then enter the transforms they have computed into a web form. The accuracy of their transforms, and thereby a measure of the accuray of their registration methods, are then automatically computed and posted to the results webpage.
Please note that we have added a new feature to the site—a tool for converting the RIRE images to DICOM format. You can find two versions—one for Linux and one for Windows— in the Download Tools. Once you have converted the files that you wish to use, they can be loaded by any tool that loads images in DICOM format.
This Retrospective Image Registration Evaluation (RIRE) project is now hosted by Kitware, Inc. using MIDAS, a collection of server/client tools for image and data assimilation.
The original RIRE project was sponsored by the National Institute of Biomedical Imaging and Bioengineering, Project Number 8R01EB002124-03, Principal Investigator, J. Michael Fitzpatrick, Vanderbilt University, Nashville, TN. Prior to RIRE, this was called the "Retrospective Registration Evaluation Project (RREP)".
- Comparision and evaluation of retrospective intermodality image registration technique, SPIE Medim'96, SPIE 2710, pp. 332-347, 1996 (text only: )
- Comparision and evaluation of retrospective intermodality image brain image registration techniques, Journal of Computer Assisted Tomography, vol.21, pp. 554-566, 1997 (text only: )
- Predicting Error in Rigid-body, Point-based Registration, IEEE Trans. Medical Image special issue on Image Registration, IEEE TMI, vol.17, pp. 694-702, 1998