TY - GEN
T1 - Developmental patterns based individualized parcellation of infant cortical surface
AU - Li, Gang
AU - Wang, Li
AU - Lin, Weili
AU - Shen, Dinggang
N1 - Funding Information:
Acknowledgements. This work was supported in part by NIH grants (MH100217, MH107815, MH108914, MH109773, and MH110274).
Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - The human cerebral cortex develops dynamically during the early postnatal stage, reflecting the underlying rapid changes of cortical microstructures and their connections, which jointly determine the functional principles of cortical regions. Hence, the dynamic cortical developmental patterns are ideal for defining the distinct cortical regions in microstructure and function for neurodevelopmental studies. Moreover, given the remarkable inter-subject variability in terms of cortical structure/function and their developmental patterns, the individualized cortical parcellation based on each infant’s own developmental patterns is critical for precisely localizing personalized distinct cortical regions and also understanding inter-subject variability. To this end, we propose a novel method for individualized parcellation of the infant cortical surface into distinct and meaningful regions based on each individual’s cortical developmental patterns. Specifically, to alleviate the effects of cortical measurement errors and also make the individualized cortical parcellation comparable across subjects, we first create a population-based cortical parcellation to capture the general developmental landscape of the cortex in an infant population. Then, this population-based parcellation is leveraged to guide the individualized parcellation based on each infant’s own cortical developmental patterns in an iterative manner. At each iteration, the individualized parcellation is gradually updated based on (1) the prior information of the population-based parcellation, (2) the individualized parcellation at the previous iteration, and also (3) the developmental patterns of all vertices. Experiments on fifteen healthy infants, each with longitudinal MRI scans acquired at six time points (i.e., 1, 3, 6, 9, 12 and 18 months of age), show that our method generates a reliable and meaningful individualized cortical parcellation based on each infant’s own developmental patterns.
AB - The human cerebral cortex develops dynamically during the early postnatal stage, reflecting the underlying rapid changes of cortical microstructures and their connections, which jointly determine the functional principles of cortical regions. Hence, the dynamic cortical developmental patterns are ideal for defining the distinct cortical regions in microstructure and function for neurodevelopmental studies. Moreover, given the remarkable inter-subject variability in terms of cortical structure/function and their developmental patterns, the individualized cortical parcellation based on each infant’s own developmental patterns is critical for precisely localizing personalized distinct cortical regions and also understanding inter-subject variability. To this end, we propose a novel method for individualized parcellation of the infant cortical surface into distinct and meaningful regions based on each individual’s cortical developmental patterns. Specifically, to alleviate the effects of cortical measurement errors and also make the individualized cortical parcellation comparable across subjects, we first create a population-based cortical parcellation to capture the general developmental landscape of the cortex in an infant population. Then, this population-based parcellation is leveraged to guide the individualized parcellation based on each infant’s own cortical developmental patterns in an iterative manner. At each iteration, the individualized parcellation is gradually updated based on (1) the prior information of the population-based parcellation, (2) the individualized parcellation at the previous iteration, and also (3) the developmental patterns of all vertices. Experiments on fifteen healthy infants, each with longitudinal MRI scans acquired at six time points (i.e., 1, 3, 6, 9, 12 and 18 months of age), show that our method generates a reliable and meaningful individualized cortical parcellation based on each infant’s own developmental patterns.
UR - http://www.scopus.com/inward/record.url?scp=85029388305&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-66182-7_8
DO - 10.1007/978-3-319-66182-7_8
M3 - Conference contribution
AN - SCOPUS:85029388305
SN - 9783319661810
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 66
EP - 74
BT - Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings
A2 - Descoteaux, Maxime
A2 - Duchesne, Simon
A2 - Franz, Alfred
A2 - Jannin, Pierre
A2 - Collins, D. Louis
A2 - Maier-Hein, Lena
PB - Springer Verlag
T2 - 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017
Y2 - 11 September 2017 through 13 September 2017
ER -
