TY - JOUR
T1 - Computational Neuroanatomy of Baby Brains
T2 - A Review
AU - Li, Gang
AU - Wang, Li
AU - Yap, Pew-Thian
AU - Wang, Fan
AU - Wu, Zhengwang
AU - Meng, Yu
AU - Dong, Pei
AU - Kim, Jaeil
AU - Feng, Shide
AU - Rekik, Islem
AU - Lin, Weili
AU - Shen, Dinggang
N1 - This work was partially supported by NIH grants (MH100217, MH107815, MH108914, MH109773, MH110274 and NS093842).
PY - 2019/1/15
Y1 - 2019/1/15
N2 - The first postnatal years are an exceptionally dynamic and critical period of structural, functional and connectivity development of the human brain. The increasing availability of non-invasive infant brain MR images provides unprecedented opportunities for accurate and reliable charting of dynamic early brain developmental trajectories in understanding normative and aberrant growth. However, infant brain MR images typically exhibit reduced tissue contrast (especially around 6 months of age), large within-tissue intensity variations, and regionally-heterogeneous, dynamic changes, in comparison with adult brain MR images. Consequently, the existing computational tools developed typically for adult brains are not suitable for infant brain MR image processing. To address these challenges, many infant-tailored computational methods have been proposed for computational neuroanatomy of infant brains. In this review paper, we provide a comprehensive review of the state-of-the-art computational methods for infant brain MRI processing and analysis, which have advanced our understanding of early postnatal brain development. We also summarize publically available infant-dedicated resources, including MRI datasets, computational tools, grand challenges, and brain atlases. Finally, we discuss the limitations in current research and suggest potential future research directions.
AB - The first postnatal years are an exceptionally dynamic and critical period of structural, functional and connectivity development of the human brain. The increasing availability of non-invasive infant brain MR images provides unprecedented opportunities for accurate and reliable charting of dynamic early brain developmental trajectories in understanding normative and aberrant growth. However, infant brain MR images typically exhibit reduced tissue contrast (especially around 6 months of age), large within-tissue intensity variations, and regionally-heterogeneous, dynamic changes, in comparison with adult brain MR images. Consequently, the existing computational tools developed typically for adult brains are not suitable for infant brain MR image processing. To address these challenges, many infant-tailored computational methods have been proposed for computational neuroanatomy of infant brains. In this review paper, we provide a comprehensive review of the state-of-the-art computational methods for infant brain MRI processing and analysis, which have advanced our understanding of early postnatal brain development. We also summarize publically available infant-dedicated resources, including MRI datasets, computational tools, grand challenges, and brain atlases. Finally, we discuss the limitations in current research and suggest potential future research directions.
KW - Brain atlas
KW - Cortical surface
KW - Infant brain
KW - Parcellation
KW - Registration
KW - Segmentation
UR - http://www.scopus.com/inward/record.url?scp=85057290031&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2018.03.042
DO - 10.1016/j.neuroimage.2018.03.042
M3 - Review article
C2 - 29574033
SN - 1053-8119
VL - 185
SP - 906
EP - 925
JO - NeuroImage
JF - NeuroImage
ER -
