==== SynthStrip dataset ======================================================= The SynthStrip dataset is a collection of magnetic resonance images (MRI) and ground-truth brain masks, gathered across an array of public sources and used to evaluate the SynthStrip brain-extraction tool: Hoopes A, Mora JS, Dalca AV, Fischl B*, Hoffmann M* (*equal contribution) SynthStrip: skull-stripping for any brain image NeuroImage, 260, 119474, 2022 https://doi.org/10.1016/j.neuroimage.2022.119474 More information on the SynthStrip tool is available on the project website https://w3id.org/synthstrip ==== Dataset breakdown ======================================================== The images in this data collection span across a range of MRI contrasts, resolutions, and subject populations. A breakdown of their distribution is as follows (see the reference above for details). Dataset Modality Voxel size (mm^3) Images ========================================================= IXI T1w MRI 0.9 x 0.9 x 1.2 50 T2w MRI 0.9 x 0.9 x 1.2 50 PDw MRI 0.9 x 0.9 x 1.2 50 MRA 0.5 x 0.5 x 0.8 50 DWI 1.8 x 1.8 x 2.0 32 --------------------------------------------------------- FSM T1w MPRAGE 1.0 x 1.0 x 1.0 38 T2w 3D-SPACE 1.0 x 1.0 x 1.0 36 PDw 3D-FLASH 1.0 x 1.0 x 1.0 32 qT1 MP2RAGE 1.0 x 1.0 x 1.0 32 --------------------------------------------------------- ASL T1w MPRAGE 1.0 x 1.0 x 1.0 43 PCASL 2D-EPI 3.4 x 3.4 x 5.0 43 --------------------------------------------------------- QIN T1w 2D-FLASH 0.4 x 0.4 x 6.0 54 T2-FLAIR 2D-FSE 0.4 x 0.4 x 6.0 17 T2w 2D-FSE 1.0 x 1.0 x 5.0 39 --------------------------------------------------------- Infant T1w MPRAGE 1.0 x 1.0 x 1.0 16 --------------------------------------------------------- CIM (*) FDG PET 2.0 x 2.0 x 2.0 20 CT 0.6 x 0.6 x 1.5 20 --------------------------------------------------------- Total: 622 Each subdirectory represents an individual scan and contains an unmodified image file (image.nii.gz) and a ground-truth binary brain mask (mask.nii.gz). Subdirectory names follow a SUBSET_MODALITY_SUBJECT format. (*) As we cannot redistribute the PET and CT images from the CERMEP-IDB-MRXFDG dataset, we only include the corresponding brain masks in the native space of these scans. To obtain the images, please contact the original authors or fill out their data-request form: Ines Merida (merida@cermep.fr) https://framaforms.org/request-form-for-cermep-idb-mrxfdg-database-1637844711 ==== Validation subset ======================================================== The SynthStrip publication uses the following scans for validation, holding out all other images for testing. ixi_t1_016 ixi_t1_017 ixi_t2_016 ixi_t2_017 ixi_pd_016 ixi_pd_017 ixi_mra_016 ixi_mra_017 fsm_t2_02cd fsm_t2_24dz fsm_pd_02cd fsm_pd_24dz fsm_qt1_02cd fsm_qt1_24dz asl_t1_110 asl_t1_120 asl_epi_110 asl_epi_120 qin_t1_01 qin_t1_02 qin_flair_01 qin_flair_02 qin_t2_01 qin_t2_02 ==== License ================================================================== You can use the IXI images under a Creative Commons Attribution-ShareAlike 4.0 International Licence (CC BY-SA 4.0). We distribute all other content of the SynthStrip dataset under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by-sa/4.0/ https://creativecommons.org/licenses/by/4.0/ ==== References =============================================================== If you find this dataset useful, please cite the SynthStrip reference at the top and any relevant references below to credit the original authors of the source datasets we obtained the images from. Information eXtraction from Images (IXI): IXI Dataset Biomedical Image Analysis Group, Imperial College London https://brain-development.org/ixi-dataset FreeSurfer Maintenance (FSM): A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images Greve DN, Billot B, Cordero D, Hoopes A, Hoffmann M, Dalca AV, Fischl B, Iglesias JE, Augustinack JC NeuroImage, 244, 118610, 2021 https://doi.org/10.1016/j.neuroimage.2021.118610 In-house HCP-A pseudo-continuous arterial spin labeling (ASL): Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects Harms MP, Somerville LH, Ances BM, Andersson J, Barch DM, et al. NeuroImage, 183, 972-84, 2018 https://doi.org/10.1016/j.neuroimage.2018.09.060 Characterizing cerebral hemodynamics across the adult lifespan with arterial spin labeling MRI data from the Human Connectome Project-Aging Juttukonda MR, Li B, Almaktoum R, Stephens KA, Yochim KM, Yacoub E, Buckner RL, Salat DH NeuroImage, 230, 117807, 2021 https://doi.org/10.1016/j.neuroimage.2021.117807 QIN GBM Treatment Response from The Cancer Imaging Archive (QIN): Mamonov AB, Kalpathy-Cramer J Data From QIN GBM Treatment Response The Cancer Imaging Archive https://doi.org/10.7937/K9/TCIA.2016.nQF4gpn2 Prah MA, Stufflebeam SM, Paulson ES, Kalpathy-Cramer J, Gerstner ER, Batchelor TT, Barboriak DP, Rosen BR, Schmainda KM Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma American Journal of Neuroradiology, 36 (9), 1654-61, 2015 https://doi.org/10.3174/ajnr.A4374 Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository Journal of Digital Imaging, 26 (6), 1045-57, 2013 https://doi.org/10.1007/s10278-013-9622-7 Infant subjects from Boston Children's Hospital (Infant): De Macedo Rodrigues K, Ben-Avi E, Sliva DD, Choe MS, Drottar M, Wang R, Fischl B, Grant PE, Zollei L A FreeSurfer-compliant consistent manual segmentation of infant brains spanning the 0-2 year age range Frontiers in Human Neuroscience, 9, 21, 2015 https://doi.org/10.3389/fnhum.2015.00021 CERMEP-IDB-MRXFDG (CIM): Merida I, Jung J, Bouvard S, Le Bars D, Lancelot S, Lavenne F, Bouillot C, Redoute J, Hammers A, Costes N CERMEP-IDB-MRXFDG: a database of 37 normal adult human brain [18F]FDG PET, T1 and FLAIR MRI, and CT images available for research EJNMMI Research, 11, 91, 2021 https://doi.org/10.1186/s13550-021-00830-6 ==== Changes ================================================================== 2022-03-16 (v1.0): * Released initial dataset. 2022-03-17 (v1.1): * Updated README and data subsets included. 2022-07-26 (v1.2): * Added the Infant data. * Listed the validation scans used in the publication. 2022-12-16 (v1.3): * Added the FSM data and CIM masks. * Added missing asl_epi_115 image. * Specified license.