iBEAT V2.0 Cloud - How-to-cite

iBEAT V2.0: Infant Brain Extraction and Analysis Toolbox

Please cite the following papers if you use the results provided by iBEAT V2.0:

L. Wang, Z. Wu, L. Chen, Y. Sun, W. Lin, G. Li , "iBEAT V2.0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction," Nature Protocols, vol. 18, pp. 1488–1509, 2023.
L. Wang, G. Li, F. Shi, X. Cao, C. Lian, D. Nie, et al., "Volume-based analysis of 6-month-old infant brain MRI for autism biomarker identification and early diagnosis," in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2018, pp. 411-419. [ Code: Caffe prototxt ]
G. Li, J. Nie, L. Wang, F. Shi, J. H. Gilmore, W. Lin, et al., "Measuring the dynamic longitudinal cortex development in infants by reconstruction of temporally consistent cortical surfaces," Neuroimage, vol. 90, pp. 266-279, 2014.
G. Li, L. Wang, P.-T. Yap, F. Wang, Z. Wu, Y. Meng, et al., "Computational neuroanatomy of baby brains: A review," NeuroImage, vol. 185, pp. 906-925, 2018.
G. Li, L. Wang, F. Shi, J. Gilmore, W. Lin, D. Shen, "Construction of 4D high-definition cortical surface atlases of infants: Methods and applications," Medical Image Analysis, 25: 22-36, 2015.

iBEAT V2.0 is a toolbox for processing pediatric brain MR images, using multimodality (including T1w and T2w) or single-modality. The software is developed by the Developing Brain Computing Lab, and the Brain Research through Analysis and Informatics of Neuroimaging (BRAIN) Lab in the University of North Carolina at Chapel Hill.

Dr. Li Wang: li_wang@med.unc.edu
Dr. Gang Li: gang_li@med.unc.edu
130 Mason Farm Road
Chapel Hill, NC 27599
United States