TY - GEN
T1 - Cortical foldingprints for infant identification
AU - Duan, Dingna
AU - Xia, Shunren
AU - Wu, Zhengwang
AU - Wang, Fan
AU - Wang, Li
AU - Lin, Weili
AU - Gilmore, John H.
AU - Shen, Dinggang
AU - Li, Gang
N1 - Funding Information:
This work was partially supported by NIH grants (MH100217, MH107815, MH108914, MH109773, MH110274, MH116225, MH117943, MH070890, MH064065, and HD053000).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Cortical folding of the adult brain is highly convoluted and encodes inter-subject variable characteristics. Recent studies suggest that it is useful for individual identification in adults. However, little is known about whether the infant cortical folding, which undergoes dynamic postnatal development, can be used for individual identification. To fill this gap, we propose to explore cortical folding patterns for infant subject identification. This study thus aims to address two important questions in neuroscience: 1) whether the infant cortical folding is unique for individual identification; and 2) considering the region-specific inter-subject variability, which cortical regions are more distinct and reliable for infant identification. To this end, we propose a novel discriminative descriptor of regional cortical folding based on multi-scale analysis of curvature maps via spherical wavelets, called FoldingPrint. Experiments are carried out on a large longitudinal dataset with 1,141 MRI scans from 472 infants. Despite the dramatic development in the first two years, successful identification of 1-year-olds and 2-year-olds using their neonatal cortical folding (with accuracy >98%) indicates the effectiveness of the proposed method. Moreover, we reveal that regions with high identification accuracy and large inter-subject variability mainly distribute in high-order association cortices.
AB - Cortical folding of the adult brain is highly convoluted and encodes inter-subject variable characteristics. Recent studies suggest that it is useful for individual identification in adults. However, little is known about whether the infant cortical folding, which undergoes dynamic postnatal development, can be used for individual identification. To fill this gap, we propose to explore cortical folding patterns for infant subject identification. This study thus aims to address two important questions in neuroscience: 1) whether the infant cortical folding is unique for individual identification; and 2) considering the region-specific inter-subject variability, which cortical regions are more distinct and reliable for infant identification. To this end, we propose a novel discriminative descriptor of regional cortical folding based on multi-scale analysis of curvature maps via spherical wavelets, called FoldingPrint. Experiments are carried out on a large longitudinal dataset with 1,141 MRI scans from 472 infants. Despite the dramatic development in the first two years, successful identification of 1-year-olds and 2-year-olds using their neonatal cortical folding (with accuracy >98%) indicates the effectiveness of the proposed method. Moreover, we reveal that regions with high identification accuracy and large inter-subject variability mainly distribute in high-order association cortices.
KW - Cortical folding
KW - Individual identification
KW - Infant
KW - Multi-scale curvatures
UR - http://www.scopus.com/inward/record.url?scp=85073897025&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2019.8759429
DO - 10.1109/ISBI.2019.8759429
M3 - Conference contribution
AN - SCOPUS:85073897025
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 396
EP - 399
BT - ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
PB - IEEE Computer Society
T2 - 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
Y2 - 8 April 2019 through 11 April 2019
ER -