20.9.5.1 Brain Development Analysis, Infant Brain

Chapter Contents (Back)
Brain Development.

Batchelor, P.G., Castellano-Smith, A.D., Hill, D.L.G., Hawkes, D.J., Cox, T.C.S., Dean, A.F.,
Measures of folding applied to the development of the human fetal brain,
MedImg(21), No. 8, August 2002, pp. 953-965.
IEEE Top Reference. 0301
BibRef

Thomaz, C.E., Boardman, J.P., Counsell, S., Hill, D.L.G., Hajnal, J.V., Edwards, A.D., Rutherford, M.A., Gillies, D.F., Rueckert, D.,
A multivariate statistical analysis of the developing human brain in preterm infants,
IVC(25), No. 6, 1 June 2007, pp. 981-994.
Elsevier DOI 0704
Multivariate statistics; Small sample size; Brain images; Preterm infants BibRef

Pienaar, R., Fischl, B., Caviness, V., Makris, N., Grant, P.E.,
A methodology for analyzing curvature in the developing brain from preterm to adult,
IJIST(18), No. 1, 2008, pp. 42-68.
DOI Link 0806
BibRef

Mutsvangwa, T.E.M., Smit, J., Hoyme, H.E., Kalberg, W., Viljoen, D.L., Meintjes, E.M., Douglas, T.S.,
Design, Construction, and Testing of a Stereo-Photogrammetric Tool for the Diagnosis of Fetal Alcohol Syndrome in Infants,
MedImg(28), No. 9, September 2009, pp. 1448-1458.
IEEE DOI 0909
BibRef

Douglas, T.S.[Tania S.], Martinez, F.[Fernando], Meintjes, E.M.[Ernesta M.], Vaughan, C.L.[Christopher L.], Viljoen, D.L.[Denis L.],
A Photogrammetric Method for the Assessment of Facial Morphology in Fetal Alcohol Syndrome Screening,
PCV02(B: 48). 0305
BibRef

Aljabar, P., Wolz, R., Srinivasan, L., Counsell, S.J., Rutherford, M.A., Edwards, A.D., Hajnal, J.V., Rueckert, D.,
A Combined Manifold Learning Analysis of Shape and Appearance to Characterize Neonatal Brain Development,
MedImg(30), No. 12, December 2011, pp. 2072-2086.
IEEE DOI 1112
BibRef

Zhu, H., Styner, M.[Martin], Tang, N., Liu, Z., Lin, W., Gilmore, J.H.[John H.],
FRATS: Functional Regression Analysis of DTI Tract Statistics,
MedImg(29), No. 4, April 2010, pp. 1039-1049.
IEEE DOI 1003
BibRef

Xu, S.[Shun], Styner, M.[Martin], Gilmore, J.H.[John H.], Piven, J.[Joseph], Gerig, G.[Guido],
Multivariate nonlinear mixed model to analyze longitudinal image data: MRI study of early brain development,
MMBIA08(1-8).
IEEE DOI 0806
See also Toward a Comprehensive Framework for the Spatiotemporal Statistical Analysis of Longitudinal Shape Data. BibRef

Jespersen, S.N., Leigland, L.A., Cornea, A., Kroenke, C.D.,
Determination of Axonal and Dendritic Orientation Distributions Within the Developing Cerebral Cortex by Diffusion Tensor Imaging,
MedImg(31), No. 1, January 2012, pp. 16-32.
IEEE DOI 1201
BibRef

Serag, A., Kyriakopoulou, V., Rutherford, M.A., Edwards, A.D., Hajnal, J.V., Aljabar, P., Counsell, S.J., Boardman, J.P., Rueckert, D.,
A Multi-channel 4D Probabilistic Atlas of the Developing Brain: Application to Fetuses and Neonates,
BMVA(2012), No. 3, 2012, pp. 1-14.
PDF File. 1209
BibRef

Makropoulos, A., Gousias, I.S., Ledig, C., Aljabar, P., Serag, A., Hajnal, J.V., Edwards, A.D., Counsell, S.J., Rueckert, D.,
Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain,
MedImg(33), No. 9, September 2014, pp. 1818-1831.
IEEE DOI 1410
biomedical MRI BibRef

Zhang, Y., Shi, F., Wu, G., Wang, L., Yap, P.T., Shen, D.,
Consistent Spatial-Temporal Longitudinal Atlas Construction for Developing Infant Brains,
MedImg(35), No. 12, December 2016, pp. 2568-2577.
IEEE DOI 1612
Brain modeling BibRef

Hong, Y., Kim, J., Chen, G., Lin, W., Yap, P., Shen, D.,
Longitudinal Prediction of Infant Diffusion MRI Data via Graph Convolutional Adversarial Networks,
MedImg(38), No. 12, December 2019, pp. 2717-2725.
IEEE DOI 1912
Convolution, Magnetic resonance imaging, Laplace equations, Chebyshev approximation, Training, Generators, Loss measurement, early brain development BibRef

Zille, P., Calhoun, V.D., Stephen, J.M., Wilson, T.W., Wang, Y.,
Fused Estimation of Sparse Connectivity Patterns From Rest fMRI: Application to Comparison of Children and Adult Brains,
MedImg(37), No. 10, October 2018, pp. 2165-2175.
IEEE DOI 1810
Correlation, Sparse matrices, Estimation, Matrix decomposition, Brain, Data mining, Time series analysis, Sparse models, brain development BibRef

Zhang, C., Adeli, E., Wu, Z., Li, G., Lin, W., Shen, D.,
Infant Brain Development Prediction With Latent Partial Multi-View Representation Learning,
MedImg(38), No. 4, April 2019, pp. 909-918.
IEEE DOI 1904
Data models, Brain modeling, Pediatrics, Predictive models, Task analysis, Magnetic resonance imaging, multi-view learning BibRef

Zhang, A., Cai, B., Hu, W., Jia, B., Liang, F., Wilson, T.W., Stephen, J.M., Calhoun, V.D., Wang, Y.,
Joint Bayesian-Incorporating Estimation of Multiple Gaussian Graphical Models to Study Brain Connectivity Development in Adolescence,
MedImg(39), No. 2, February 2020, pp. 357-365.
IEEE DOI 2002
Aldolescence, fMRI, brain development, brain functional connectivity, joint estimation BibRef

Içer, S.[Semra],
Functional connectivity differences in brain networks from childhood to youth,
IJIST(30), No. 1, 2020, pp. 75-91.
DOI Link 2002
age-related brain maturation, healthy childhood development, resting-state networks BibRef


Fishbaugh, J.[James], Styner, M.[Martin], Grewen, K.[Karen], Gilmore, J.[John], Gerig, G.[Guido],
Spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development,
MFCA19(174-185).
Springer DOI 1912
BibRef

Shukla, P., Gupta, T., Saini, A., Singh, P., Balasubramanian, R.,
A Deep Learning Frame-Work for Recognizing Developmental Disorders,
WACV17(705-714)
IEEE DOI 1609
Atmospheric modeling, Autism, Computer vision, Face, Genetics, Neural networks, Support, vector, machines BibRef

Meng, Y.[Yu], Li, G.[Gang], Gao, Y.[Yaozong], Gilmore, J.H.[John H.], Lin, W.[Weili], Shen, D.G.[Ding-Gang],
Subject-Specific Estimation of Missing Cortical Thickness Maps in Developing Infant Brains,
MCV15(83-92).
Springer DOI 1608
BibRef

Alansary, A., Soliman, A., Nitzken, M., Khalifa, F., Elnakib, A., Mostapha, M., Casanova, M.F., El-Baz, A.,
An integrated geometrical and stochastic approach for accurate infant brain extraction,
ICIP14(3542-3546)
IEEE DOI 1502
Brain modeling BibRef

Lanche, S.[Stéphanie], Darvann, T.A.[Tron A.], Ólafsdóttir, H.[Hildur], Hermann, N.V.[Nuno V.], van Pelt, A.E.[Andrea E.], Govier, D.[Daniel], Tenenbaum, M.J.[Marissa J.], Naidoo, S.[Sybill], Larsen, P.[Per], Kreiborg, S.[Sven], Larsen, R.[Rasmus], Kane, A.A.[Alex A.],
A Statistical Model of Head Asymmetry in Infants with Deformational Plagiocephaly,
SCIA07(898-907).
Springer DOI 0706
BibRef

Yu, P.[Peng], Yeo, B.T.T.[Boon Thye Thomas], Grant, P.E.[P. Ellen], Fischl, B.[Bruce], Golland, P.[Polina],
Cortical Folding Development Study based on Over-Complete Spherical Wavelets,
MMBIA07(1-8).
IEEE DOI 0710
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Brain, Cortex, General Segmentation Issues .


Last update:Feb 20, 2020 at 21:34:09