Release Name: 0.3.2

Notes:
mri_reface Docker:
This Docker image replaces face and ear imagery in brain MRI/PET/CT with an average face, to help prevent potential re-identification

By: Christopher G. Schwarz and Carl M. Prakaashana, schwarz.christopher@mayo.edu
For details, please see this paper and cite it if you use it in your work:
Christopher G. Schwarz, Walter K. Kremers, Heather J. Wiste, Jeffrey L. Gunter, Prashanthi Vemuri, Anthony J. Spychalla, Kejal Kantarci, Aaron P. Schultz, Reisa A. Sperling, David S. Knopman, Ronald C. Petersen, Clifford R. Jack. Changing the face of neuroimaging research: Comparing a new MRI de-facing technique with popular alternatives. In: NeuroImage 231, 2021. https://doi.org/10.1016/j.neuroimage.202...
For PET/CT support: Christopher G. Schwarz, Walter K. Kremers, Val J. Lowe, Marios Savvides, Jeffrey L. Gunter, Matthew L. Senjem, Prashanthi Vemuri, Kejal Kantarci, David S. Knopman, Ronald C. Petersen, Clifford R. Jack. Face recognition from research brain PET: An unexpected PET problem. In: NeuroImage 258, 2022. https://doi.org/10.1016/j.neuroimage.202...
This software works only with Docker environment installed. First, run ''''docker load < mri_reface_docker_image''''. You should then run it through the included run_mri_reface_docker.sh rather than entering the Docker environment directly. The Docker image includes all dependencies of mri_reface and does not require any software be added to the user''''s system other than Docker.
mri_reface Docker allows Nifti (.nii) or DICOM inputs. If the user provides a .nii file, mri_reface Docker will output a refaced .nii file and before/after face renders. If the user provides a DICOM directory as an input, in mri_reface Docker will convert the image into .nii, reface the .nii image, convert the .nii image back to DICOM (copying all unaffected tags from the original DICOM to the new DICOM) and tag the DICOM files as being de-faced. The output for DICOM input include the refaced .nii, before/after face renders, and the refaced DICOM files. The direct-DICOM workflow is NOT recommended for PET inputs, as it will not account for motion across frames.
For .nii inputs, the input path should be to the .nii file itself. For DICOM inputs, the input path should be to a directory, this directory should contain ONLY the DICOM files for the image (a single series).
This work was supported by: NIH grants R01 AG068206, U01 AG006786, P50 AG016574, R01 AG034676, R37 AG011378, R01 AG041851, R01 NS097495, R01 AG056366, U01 NS100620; The GHR Foundation; The Elsie and Marvin Dekelboum Family Foundation; The Alexander Family Alzheimer''''s Disease Research Professorship of the Mayo Clinic; The Liston Award; The Schuler Foundation; and The Mayo Foundation for Medical Education and Research. We also gratefully acknowledge the support of NVIDIA Corporation with the donation of a Quadro P6000 GPU used in generating 3D facial reconstructions for this research. We also thank AVID Radiopharmaceuticals, Inc., for their support in supplying Flortaucipir precursor, chemistry production advice, and FDA regulatory cross-filing permission and documentation needed for this work.
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