BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution
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<strong>BigBrain-MR</strong> is a novel digital phantom with realistic anatomical detail up to 100-µm resolution, including multiple MRI contrasts and properties that affect image generation. This phantom was generated from the publicly available BigBrain histological dataset and from lower-resolution in-vivo 7T-MRI data, using a new image processing framework that allows mapping the general properties of in-vivo data into the fine anatomical scale of BigBrain. The <strong>dataset</strong> includes: BigBrain original contrast and a new atlas with 20 ROIs; T<sub>1</sub>-weighted image and T<sub>1</sub> map; T<sub>2</sub>*-weighted images and R<sub>2</sub>* map; Magnetic susceptibility map (QSM); Background magnetic field map; Complex coil sensitivity maps (32ch-receive RF array); Bias field map. Information about each image/map (including data type and amplitude scaling) is provided in <em>data_info.txt</em>. Additionally, we have included a script with <strong>usage examples</strong> in Python that illustrate how the data can be loaded, processed and combined for diverse simulation purposes. BigBrain-MR is presented, described and tested in the following <strong>peer-reviewed article</strong>: C. Sainz Martinez, M. Bach Cuadra, J. Jorge. <em>BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development</em>. NeuroImage 2023. <strong>DOI:</strong> 10.1016/j.neuroimage.2023.120074
