Yuhui Du Personal Website-Intelligent Analysis of Medical Image
Address：Taiyuan, China
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IABC（Intelligent Analysis of Brain Connectivity）toolbox
时间：2022-02-10 19:28:55 来源： 点击：[638]
Software introduction:
Based on the Matlab interactive development environment, the IAMI (Intelligent Analysis of Medical Image) laboratory led by Professor Du Yuhui from the School of Computer and Information Technology of Shanxi University developed the IABC (Intelligent Analysis of Brain Connectivity) toolbox. We release the IABC toolbox here for use by researchers in the field of brain science. Currently, the toolbox integrates our previously proposed GIG-ICA (Group information guided independent component analysis) and NeuroMark (An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders). The toolbox can analyze the brain functional MRI data of multiple subjects at the same time, and can calculate the brain functional networks of individual subjects, the time series related to the brain functional networks, and the functional network connectivity (FNC). Using our toolbox, brain functional networks and related information can be visualized as well, and the estimated measures can be used by researchers for subsequent statistical analysis, clustering, and classification studies. We will periodically upgrade the IABC toolbox, which will include more advanced brain connectivity analysis methods developed by the IAMI Laboratory.
Sharing files：
| Download | Version | Upload Time |
 IABC.rar | Version 1 | 2022.02.22 |
Version 2 | 2022.04.11 | |
Version 3 | 2022.05.06 | |
Version 4 | 2022.05.31 | |
Version 5 | 2022.11.02 | |
Version 6 | 2022.11.29 | |
Version 7 | 2023.05.26 |
Please cite as:
[1] Du, Y. H. and Y. Fan (2013). "Group information guided ICA for fMRI data analysis." Neuroimage 69: 157-197.
[2] Du, Y. H., G. D. Pearlson, J. Y. Liu, J. Sui, Q. B. Yu, H. He, E. Castro and V. D. Calhoun (2015). "A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: application to schizophrenia, bipolar, and schizoaffective disorders." Neuroimage 122: 272-280.
[3] Du, Y. H., E. A. Allen, H. He, J. Sui, L. Wu and V. D. Calhoun (2016). "Artifact removal in the context of group ICA: A comparison of single-subject and group approaches." Hum Brain Mapp 37(3): 1005-1025.
[4] Du, Y. H., Fu, Z. N., Sui, J., et al. (2020). “NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders.” NeuroImage: Clinical 28: 102375.
[5] Du, Y., Y. Kong and X. He (2023). "IABC: A Toolbox for Intelligent Analysis of Brain Connectivity." Neuroinformatics.