Litcius/Paper detail

Diffusion Imaging in the Post HCP Era

Steen Moeller, Pramod Kumar Pisharady, Jesper Andersson, Mehmet Akçakaya, Noam Harel, Ruoyun Ma, Xiaoping Wu, Essa Yacoub, Christophe Lenglet, Kǎmil Uǧurbil

2020Journal of Magnetic Resonance Imaging29 citationsDOIOpen Access PDF

Abstract

Diffusion imaging is a critical component in the pursuit of developing a better understanding of the human brain. Recent technical advances promise enabling the advancement in the quality of data that can be obtained. In this review the context for different approaches relative to the Human Connectome Project are compared. Significant new gains are anticipated from the use of high-performance head gradients. These gains can be particularly large when the high-performance gradients are employed together with ultrahigh magnetic fields. Transmit array designs are critical in realizing high accelerations in diffusion-weighted (d)MRI acquisitions, while maintaining large field of view (FOV) coverage, and several techniques for optimal signal-encoding are now available. Reconstruction and processing pipelines that precisely disentangle the acquired neuroanatomical information are established and provide the foundation for the application of deep learning in the advancement of dMRI for complex tissues. Level of Evidence: 3 Technical Efficacy Stage: Stage 3.

Topics & Concepts

Computer scienceHuman Connectome ProjectContext (archaeology)Diffusion MRIDiffusionArtificial intelligenceField (mathematics)Deep learningEncoding (memory)Magnetic resonance imagingNeuroscienceFunctional connectivityGeologyMedicinePure mathematicsPhysicsMathematicsRadiologyThermodynamicsBiologyPaleontologyAdvanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity Studies