Figure 1.

A comprehensive experimental framework for subject motion simulation to systematically evaluate the outcome of different motion correction choices commonly used by the scientific community on HARDI-based reconstructions and tractography. (A) A human brain HARDI data were acquired from a well-controlled motion experiment. (a.1) Acquired DWIs were preprocessed to obtain nearly noise-free and motion-free datasets. (a.2) For automated tractography selection and the quantification of whole brain connectivity, a subject-specific unbiased atlas was constructed via DTI-derived data from HARDI sequences resulting in a tensor atlas, where we can define a detailed parcelation of neuroanatomical structures, and map it back to each raw scan. (B) Noticeable motion was then simulated by randomly mixing gradients from the acquired datasets. (C) Motion correction involves four main decision variables where each distinct combination of choices defines a correction scheme. (D) Reconstruction of a corrected or motion-free dataset entails reconstructing the voxel-wise fiber orientation distribution functions, detecting local (voxel-wise) fiber orientation, preforming whole brain tractography, and automatically selecting anatomical pathways. (E) The evaluation of the effect of a motion correct scheme has been investigated based on voxel-wise metrics, global brain connectivity metric, and tract-based metric.