[1] Toga A.W., Thompson P., Multimodal brain atlases, Book chapter on biomedical image database; 1999, The Kluwer Academic Press.
[2] Mazziotta J.C., Toga A.W., Evans A., Fox P., Lancaster J., A probabilistic atlas of the human brain: theory and rationale for its development; The International Consortium for Brain Mapping (ICBM), Neuroimage, 1995; 2: 89-101.
[3] Joshi S., Davis B., Jomier M., Gerig G., Unbiased diffeomorphic atlas construction for computational anatomy; Neuroimage, 2004; 23 (1): 151-160.
[4] Brodmann K. , Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues, 1909, Barth, Leipzig, In: Some Papers on the Cerebral Cortex, translated as: On the Comparative Localization of the Cortex, 201-230, Thomas, Springfield, IL, 1960.
[5] Toga A.W., Mazziotta J.C., Brain Mapping: The Methods; 1996, Academic Press.
[6] Thompson P.M., Mega M.S., Toga A.W., Disease-Specific Brain Atlases, Book Chapter in: Brain Mapping: The Disorders; 2000, Academic Press.
[7] Guimond A., Meunier J., Thirion J.P., Average brain models: a convergence study; Computer Vision and Image Understanding, 2000; 77(2): 192–210.
[8] Evans A.C., Collins D.L, Mills S.R., Brown E.D., Kelly R.L., Peters T.M., 3D statistical neuroanatomical models from 305 MRI volumes; IEEE Nuclear Science Symposium, Medical Imaging Conference, 1995; pp: 1813–1817.
[9] Bluml S., Friedlich P., Erberich S., Wood J.C., Seri I., Nelson M.D., MR imaging of newborns by using an MR-compatible incubator with integrated radiofrequency coils: initial experience; Radiology, 2004; 231: 594-601.
[10] Jones R.A., Palasis S., Grattan-Smith J.D., MRI of the neonatal brain: optimization of spin-echo parameters; AJR Am J Roentgenol. , 2004, 182: 367-372.
[11] Muzik O., Chugani D.C., Juhasz C., Shen C., Chugani H.T., Statisticalparametric mapping: assessment of application in children; Neuroimage, 2000; 12: 538-549.
[12] Burgund E.D., Kang H.C., Kelly J.E., Buckner R.L., Snyder A.Z., Petersen S.E., Schlaggar B.L., The feasibilityof a common stereotactic space for children and adults in fMRI studies of development; Neuroimage, 2002: 1:184-200.
[13] Wilke M., Schmithorst V.J., Holland S.K., Assessment of spatial normalization of whole-brain magnetic resonance images in children; Human Brain Mapping, 2002; 17: 48-60.
[14] Wilke M., Schmithorst V.J., Holland S.K., Normative pediatric brain data for spatial normalization and segmentation differs from standard adult data; Magn Reson Med, 2003; 50:749-757.
[15] Gaillard W.D., Grandin C.B., Xu B., Developmental aspects of pediatric fMRI: considerations for image acquisition, analysis, and interpretation; Neuroimage, 2001; 13: 239-249.
[16] Ketonen L.M., Hiwatashi A., Sidhu R., Westesson P.L., Pediatric brain and spine: an atlas of MRI and spectroscopy; 2005; Springer-Verlag, Berlin Heidelberg.
[17] Dehaene-Lambertz G., Dehaene S., Hertz-Pannier L., Functional neuroimaging of speech perception in infants; Science, 2002; 298: 2013-2015.
[18] Prastawa M., Gilmore J.H., Lin W., Gerig G., Automatic segmentation of MR images of the developing newborn brain; Medical Image Anal, 2005; 9: 457-466.
[19] Kazemi K., Abrishami Moghaddam H., Grebe R., Gondry-Jouet C., Wallois F., A neonatal atlas template for spatial normalization of whole-brain Magnetic Resonance Images of newborns: preliminary results; Neuroimage, 2007; 37: 463-473.
[20] Kazemi K., Ghadimi S., Abrishami Moghaddam H., Grebe R., Gondry-Jouet C., Wallois F., Neonatal probabilistic models for brain, CSF and skull using T1-MRI data: Preliminary results; 30th Annual International Conference of theIEEE EMBS, 2008; PP: 3892-3895, Vancouver, BC.
[21] کاظمی کامران، نوری زاده نگار، شاهوران زهرا، ابریشمی مقدم حمید، گرب راینهارد، والوا فابریس، طراحی و ساخت اطلس آماری دیجیتال مغزی نوزادان، هجدهمین کنفرانس مهندسی برق ایران، اردیبهشت 89، اصفهان، ایران.
[22] Shi F., Yap P., Fan Y., Gilmore J.H., Lin W., Dinggang Shen, Construction of multi-region-multi-reference atlases for neonatal brain MRI segmentation; NeuroImage, 2010; 51: 684–693.
[23] Shi F., Yap P., Wu G., Jia H., Gilmore J., Lin W., Shen D., Infant brain atlases from neonates to 1- and 2-year-olds. PLoS One 6 (4), e18746, 2011.
[24] Murgasova M., Aljabar P., Srinivasan L., Edwards D., Hajnal J., Rueckert D., Construction of a dynamic 4D probabilistic atlas for the developing brain, MIUA, 2009.
[25] Murgasova M.K., Aljabar P., Srinivasan L., Counsell S.J., Doria V., Serag A., Gousias I.S., Boardman J.P., Rutherford M.A., Edwards A.D., Hajnal J.V., Rueckert D., A dynamic 4D probabilistic atlas of the developing brain; NeuroImage, 2011; 54(4): 2750-2763.
[26] Oishi K., Mori S., Donohue P.K., Ernst Th., Anderson L., Buchthal S., Faria A., Jiang H., Li X., Miller M.I., van Zijl P.C.M., Chang L., Multi-contrast human neonatal brain atlas: Application to normal neonate development analysis; NeuroImage , 2011; 56: 8–20
[27] Serag A., Aljabar P., Counsell S., Boardman J., Hajnal J.V., Rueckert D., Construction Of A 4d Atlas Of The Developing Brain Using Non-Rigid Registration, Biomedical Imaging: From Nano to Macro; IEEE International Symposium, 2011; pp: 1532 – 1535.
[28] Serag A., Aljabar P., Ball G., Counsell S.J., Boardman J.P., Rutherford M.A., Edwards A.D., Hajnal J.V., Rueckert D., Construction of a Consistent High-Definition Spatio-Temporal Atlas of the Developing Brain using Adaptive Kernel Regression; NeuroImage, Available online October 2011.
[29] Thompson P.M., Toga A.W., Detection, visualization and animation of abnormal anatomic structure with a deformable probabilistic brain atlas based on random vector field transformation; Medical Image Annual, 1995; 1(4): 271–294.
[30] Avants B., Gee J.C., Geodesic estimation for large deformation anatomical shape averaging and interpolation; Neuroimage, 2004; 23(1): 139-150.
[31] Hill D., Hajnal J., Rueckert D., Smith S., Hartkens T., McLeish K., A dynamic brain atlas. In: Dohi, D., Kikinis, R. (Eds.); Medical Image Computing and Computer-Assisted Intervention 2002; LNCS 2488, pp: 532–539.
[32] Talairach J., Tournoux P., Co-planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System - an Approach to Cerebral Imaging; 1988, Thieme Medical Publishers, New York.
[33] http://www.bic.mni.mcgill.ca/brainweb
[34] Cootes T.F., Taylor C.J., Cooper D.H., Graham J., Active Shape Models: Their Training and Application; Computer Vision and Image Understanding, 1995; 61(1): 38-59.
[35] Cootes T.F., Edwards C.J., Taylor C.J., Active Appearance Model; European Conference on Computer Vision, 1998; 2: 484-498.
[36] Rueckert D., Frangi A.F., Schnabel J.A., Automatic Construction of 3D Statistical Deformation Models of the Brain Using Nonrigid Registration; In Fourth Int. Conf. on Medical Image Computing and Computer Assisted Intervention, LNCS, 2001; 2208: 74-84, Springer.
[37] امامی میبدی محمدعلی، تشریح موضعی و مصور مغز و نخاع، چاپ دوم، انتشارات اشارت، 1387.
[38] Brett M., Johnsrude I.S., Owen A.M., The problem of functional localization in the human brain; 2002, Macmillan magazines.
[39] Woods R.P., Grafton S.T., Watson J.D.G., Sicotte N.L., Mazziotta J.C., Automated image registration: II. Intersubject validation of linear and nonlinear models; J. Computer Assisted Tomography, 1998; 22(1): 153-65.
[40] Duta N., Sonka M., Segmentation and Interpretation ofMR Brain Images: An Improved Active Shape Model; IEEE Transactions on Medical Imaging, 1998; 17(6).
[41] Kazemi K., Grebe R., Abrishami Moghaddam H., Lagadec P., Gondry-Jouet C., Wallois F., Design of a Digital Phantom of the Neonatal Brain; 29th Annual International Conference of the IEEE EMBS, Aug. 2007; pp: 5509 - 5512.
[42] Kazemi K., Abrishami Moghadam H., Grebe R., Gondry-Jouet C., Wallois F., Design and construction of a brain phantom to simulate neonatal MR images; Computerized Medical Imaging and Graphics, 2011; 35: 237–250.
[43] Kazemi K., Grebe R., Abrishami Moghadam H., Wallois F., Gondry-Jouet C., Steps towards a newborns MRI head atlas and model; Journal of Clinical Neurophysiology, Sep. 2008; 119(9): 120.
[44] Ashburner J., Friston K.J., Unified segmentation; Neuroimage, 2005; 26: 839-851.
[45] Zhao M., Yan H., Adaptive thresholding method for binarization blueprint images. Fifth International Symposium on Signal Processing and its Applications; ISSPA ‘99, Brisbane, Australia, 1999; pp: 931-934.
[46] Aarabi A., Kazemi K., Grebe R., Abrishami Moghaddam H., Wallois F., Detection of EEG transients in neonates and older children using a system based on dynamic time-warping template matching and spatial dipole clustering; NeuroImage, 2009; 48: 50-62.
[47] Seghers D., Dagostino E., Maes F., Vandermeulen D., Suetens P., Construction of a brain template frommr images using state-of-the-art registration and segmentationtechniques; MICCAI 2004, LNCS 3216, pp: 696-703.
[48] Weisenfeld I., Mewes U.J.A., Warfield K.S., Highly Accurate Segmentation of Brain Tissue and Subcortical Gray Matter from Newborn MRI; MICCAI 2006, LNCS 4190, pp: 199–206.
[49] Warfield S.K., Kaus M., Jolesz F.A., Kikinis R., Adaptive, template moderated, spatially varying statistical classification; Medical Image Analysis, 2000; 4(1): 43-45.
[50] Altaye M., Holland S.K., Wilke M., Gaser Ch., Infant brain probability templates for MRI segmentation and normalization; NeuroImage, 2008; 43: 721–730.
[51] Shi F., Fan Y., Tang S., Gilmore J.H., Lin W., Shen D., Neonatal brain imagesegmentation in longitudinal MRI studies; NeuroImage, 2010; 49: 391–400.
[52] Frey B.J., Dueck D., Clustering by passing messages between data points; Science, 2007; 315: 972–976.
[53] Xue H., Srinivasan L., Jianga S. et al., Automatic segmentation and reconstruction of the cortex from neonatal MRI; NeuroImage, 2007; 38(3): 461–477.
[54] Murgasova M., Hajnal J., Counsell S. et al., Template-based bias correction: Application to pediatric brain MRI; Proceedings 17th Scientific Meeting, International Society for Magnetic Resonance in Medicine, 2009; p :4672.
[55] Knickmeyer R.C., Gouttard S., Kang C., Evans D., Wilber K., A structural MRI study of human brain development from birth to 2 years; Journal of Neuroscience, 2008; 28: 12176–12182.
[56] Pham D.L., Prince J.L., An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneities; Pattern Recognition Letters, 1999; 20: 57–68.
[57] Wu G., Wang Q., Jia H., Shen D., Feature-based Groupwise Registration by Hierarchical Anatomical Correspondence Detection; Human Brain Mapping: In press, 2011.
[58] Ashburner J., Hutton Ch., Frackowiak R., Johnsrude I., Price C., Friston K., Identifying Global Anatomical Differences: Deformation-Based Morphometry; Human Brain Mapping, 1998; 6: 348–357.
[59] Dubois J., Hertz-Pannier L., Cachia A., Mangin J.F., Le Bihan D., Dehaene-Lambertz G., Structural asymmetries in the infant language and sensori-motor networks; Cereb Cortex, 2009; 19(2): 414-423.
[60] Leroy F., Glasel H., Dubois J., Hertz-Pannier L., Thirion B., Mangin J,F., Dehaene-Lambertz G., Early Maturation of the Linguistic Dorsal Pathway in Human Infants; Journal of Neuroscience, 2011; 31(4): 1500-1506.