PAGANI Toolkit: Parallel graph‐theoretical analysis package for brain network big data

• Published in: Human brain mapping Vol. 39; no. 5; pp. 1869 - 1885
• Main Authors: Du, Haixiao, Xia, Mingrui, Zhao, Kang, Liao, Xuhong, Yang, Huazhong, Wang, Yu, He, Yong
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.05.2018; John Wiley and Sons Inc
• Subjects: Adults; Algorithms; Big Data; Brain; Brain - diagnostic imaging; Brain mapping; Brain Mapping - instrumentation; Brain Mapping - methods; Central processing units; Computation; Computational neuroscience; Computer Graphics; connectome; CPUs; CUDA; Data management; Data processing; Empirical analysis; Female; fMRI; Functional magnetic resonance imaging; graph theory; Graphical user interface; Graphics processing units; hub; Humans; Image Processing, Computer-Assisted; Intelligence; Magnetic Resonance Imaging; Male; Medical imaging; Models, Neurological; Modularity; Networks; Neural Pathways - diagnostic imaging; Neuroimaging; Neurology; Oxygen - blood; Rest; Software; Spatial data; Spatial discrimination; Spatial resolution; Theoretical analysis; Young Adult; Young adults; CUDA; Big Data; fMRI; connectome; hub; graph theory

The recent collection of unprecedented quantities of neuroimaging data with high spatial resolution has led to brain network big data. However, a toolkit for fast and scalable computational solutions is still lacking. Here, we developed the PArallel Graph‐theoretical ANalysIs (PAGANI) Toolkit based...