title: "MASSIVE" brain dataset: Multiple acquisitions for standardization of structural imaging validation and evaluation.
abstract: In this work, we present the MASSIVE (Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation) brain dataset of a single healthy subject, which is intended to facilitate diffusion MRI (dMRI) modeling and methodology development.
  
  
  
  MRI data of one healthy subject (female, 25 years) were acquired on a clinical 3 Tesla system (Philips Achieva) with an eight-channel head coil. In total, the subject was scanned on 18 different occasions with a total acquisition time of 22.5 h. The dMRI data were acquired with an isotropic resolution of 2.5 mm3and distributed over five shells with b-values up to 4000 s/mm2and two Cartesian grids with b-values up to 9000 s/mm2.
  
  
  
  The final dataset consists of 8000 dMRI volumes, corresponding B0field maps and noise maps for subsets of the dMRI scans, and ten three-dimensional FLAIR, T1-, and T2-weighted scans. The average signal-to-noise-ratio of the non-diffusion-weighted images was roughly 35.
  
  
  
  This unique set of in vivo MRI data will provide a robust framework to evaluate novel diffusion processing techniques and to reliably compare different approaches for diffusion modeling. The MASSIVE dataset is made publically available (both unprocessed and processed) on www.massive-data.org. Magn Reson Med 77:1797-1809, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
authors.affiliation: Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands.
authors.forename: Martijn
authors.identifier: 0000-0003-3841-0497
authors.initials: M
authors.lastname: Froeling
authors.affiliation: Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands.
authors.forename: Chantal M W
authors.initials: CMW
authors.lastname: Tax
authors.affiliation: Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands.|Translational Imaging Group, CMIC, University College London, London, United Kingdom.
authors.forename: Sjoerd B
authors.initials: SB
authors.lastname: Vos
authors.affiliation: Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands.
authors.forename: Peter R
authors.initials: PR
authors.lastname: Luijten
authors.affiliation: Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands.
authors.forename: Alexander
authors.initials: A
authors.lastname: Leemans
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging* / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods; D016208:Databases, Factual; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D059629:Signal-To-Noise Ratio
keywords: brain dataset; diffusion MRI; evaluation; methods development; modeling; structural MRI