基于MRI的大脑皮层形态学研究
|
摘要
人类的大脑是自然界最复杂的系统。早期对大脑的研究都是通过尸检来进行的。近年来,随着脑成像技术的发展以及成像技术与数学、计算机科学、信息学、物理学等相关学科的结合,利用脑图像进行大脑形态学分析成为了脑科学研究的热点之一。本文正是利用大脑的结构磁共振影像,通过应用和改进一些传统的脑图像分析方法,对大脑皮层的形态学进行了细致的研究。本文的主要贡献如下：1.我们使用基于体素的全脑形态学分析和基于体素的全脑厚度差异分
析,考察了首发性重度抑郁症患者的皮层结构异常。我们发现了重度抑郁症患者的大脑皮层在前额叶、壳核、后扣带、楔前叶等区域的形态与正常人相比有显著的差异。这提示了,对抑郁症的皮层形态学研究应该利用多种手段进行全方位的考察,而不该只关注某个特定的脑区。
2.为了考察精神分裂症患者的皮层结构网络,我们计算了精神分裂症患者以及其对照组的皮层厚度,然后利用皮层厚度指标和大脑的AAL分区模板分别构建了两组人的脑结构网络。通过对两组人的结构网络的研究,我们发现了精神分裂症患者在右侧的前额叶和右侧的颞极间的网络连接存在异常,且精神分裂症患者的网络具有较高的局部效率和较低的全局效率。进一步的,我们对两个网络的hub节点进行研究比较,我们发现精神分裂症患者的节点异常的几个脑区大多集中在默认网络中。这个发现与他人通过功能网络对精神分裂症的研究结果相当吻合,从而为精神分裂症脑功能网络研究提供了结构上的依据。
3.提出了一种新的适用于脑磁共振影像的基于图元表示模型的自适应图像分割算法。新的算法使用了自适应的mean shift算法来提取图元表示。接着,我们提出了一种结合了脑组织结构的先验概率图谱、磁共振图像的不均匀场校正、以及马尔可夫场模型的EM迭代算法来对图像进行分割。先验概率图谱和不均匀场校正的引入使得我们的算法更适合于脑图像的分割。我们使用BrainWeb和IBSR这两个不同的公共数据集中的图像数据来检验我们的算法。实验结果表明我们的算法对不同的数据都能够得到比较准确的分割结果,具有很强的鲁棒性。
The human brain is the most complex system in the world. Early studies on the brain are mainly based on autopsy. Recently, with the development of brain imaging technology, mathematics, computer science, informatics and physics, brain morphological analysis has become one of the most investigated interests of neuroscience research.
This study mainly focused on application of the existing methods to detect abnormalities in the cerebral cortex and on improving traditional brain imaging analysis methods based on MRI. Our main contributions are as follows:
1. Using gray matter density and cortical thickness measurements, we investigated the structural abnormalities in major depressive disorder (MDD). We revealed that patients with MDD showed significant morphological abnormalities in prefrontal cortex, putamen, posterior cingulate and precuneus regions, compared with normal controls. These results indicate that MDD is a disease that involves multiple brain regions.
2. Using cortical thickness measurement, structural networks were constructed for patients with schizophrenia and normal controls respectively. Network analysis showed abnormal connectivities between prefrontal cortex and the temporal poles. In addition, patients with schizophrenia showed higher local efficiency and lower global efficiency, compared with controls. Moreover, we investigated the difference of the hub nodes in the two networks. We found that the abnormal hub nodes in schizophrenia are mainly distributed in the default mode network, which is consistent with previous functional studies. These abnormalities in structural network might be the substrates of abnormal functional connectivities.
3. We proposed an adaptive pixon represented segmentation algorithm for 3D magnetic resonance brain images. Different from traditional method, an adaptive mean shift algorithm was adopted to adaptively smooth the query image and create a pixon-based image representation. Then an expectation-maximization (EM) iterations composed of bias correction, a priori digital brain atlas information, and Markov random field (MRF) segmentation were processed. The adoption of bias correction and brain atlas made the current method more suitable for brain image segmentation than the previous pixon based segmentation algorithm. The proposed method was validated on both simulated normal brain images from BrainWeb and real brain images from the IBSR public dataset. Compared with some other popular MRI segmentation methods, the proposed method exhibited a higher degree of accuracy in segmenting both simulated and real 3D MRI brain data.
析,考察了首发性重度抑郁症患者的皮层结构异常。我们发现了重度抑郁症患者的大脑皮层在前额叶、壳核、后扣带、楔前叶等区域的形态与正常人相比有显著的差异。这提示了,对抑郁症的皮层形态学研究应该利用多种手段进行全方位的考察,而不该只关注某个特定的脑区。
2.为了考察精神分裂症患者的皮层结构网络,我们计算了精神分裂症患者以及其对照组的皮层厚度,然后利用皮层厚度指标和大脑的AAL分区模板分别构建了两组人的脑结构网络。通过对两组人的结构网络的研究,我们发现了精神分裂症患者在右侧的前额叶和右侧的颞极间的网络连接存在异常,且精神分裂症患者的网络具有较高的局部效率和较低的全局效率。进一步的,我们对两个网络的hub节点进行研究比较,我们发现精神分裂症患者的节点异常的几个脑区大多集中在默认网络中。这个发现与他人通过功能网络对精神分裂症的研究结果相当吻合,从而为精神分裂症脑功能网络研究提供了结构上的依据。
3.提出了一种新的适用于脑磁共振影像的基于图元表示模型的自适应图像分割算法。新的算法使用了自适应的mean shift算法来提取图元表示。接着,我们提出了一种结合了脑组织结构的先验概率图谱、磁共振图像的不均匀场校正、以及马尔可夫场模型的EM迭代算法来对图像进行分割。先验概率图谱和不均匀场校正的引入使得我们的算法更适合于脑图像的分割。我们使用BrainWeb和IBSR这两个不同的公共数据集中的图像数据来检验我们的算法。实验结果表明我们的算法对不同的数据都能够得到比较准确的分割结果,具有很强的鲁棒性。
The human brain is the most complex system in the world. Early studies on the brain are mainly based on autopsy. Recently, with the development of brain imaging technology, mathematics, computer science, informatics and physics, brain morphological analysis has become one of the most investigated interests of neuroscience research.
This study mainly focused on application of the existing methods to detect abnormalities in the cerebral cortex and on improving traditional brain imaging analysis methods based on MRI. Our main contributions are as follows:
1. Using gray matter density and cortical thickness measurements, we investigated the structural abnormalities in major depressive disorder (MDD). We revealed that patients with MDD showed significant morphological abnormalities in prefrontal cortex, putamen, posterior cingulate and precuneus regions, compared with normal controls. These results indicate that MDD is a disease that involves multiple brain regions.
2. Using cortical thickness measurement, structural networks were constructed for patients with schizophrenia and normal controls respectively. Network analysis showed abnormal connectivities between prefrontal cortex and the temporal poles. In addition, patients with schizophrenia showed higher local efficiency and lower global efficiency, compared with controls. Moreover, we investigated the difference of the hub nodes in the two networks. We found that the abnormal hub nodes in schizophrenia are mainly distributed in the default mode network, which is consistent with previous functional studies. These abnormalities in structural network might be the substrates of abnormal functional connectivities.
3. We proposed an adaptive pixon represented segmentation algorithm for 3D magnetic resonance brain images. Different from traditional method, an adaptive mean shift algorithm was adopted to adaptively smooth the query image and create a pixon-based image representation. Then an expectation-maximization (EM) iterations composed of bias correction, a priori digital brain atlas information, and Markov random field (MRF) segmentation were processed. The adoption of bias correction and brain atlas made the current method more suitable for brain image segmentation than the previous pixon based segmentation algorithm. The proposed method was validated on both simulated normal brain images from BrainWeb and real brain images from the IBSR public dataset. Compared with some other popular MRI segmentation methods, the proposed method exhibited a higher degree of accuracy in segmenting both simulated and real 3D MRI brain data.
引文
[1]唐孝威,杜继曾,陈学群,魏尔清,徐琴美,秦莉娟,脑科学导论.浙江大学出版社2006年.
[2]孙久荣,脑科学导论.北京大学出版社2001年.
[3]李振平,临床中枢神经解剖学.北京科学出版社2003年.
[4]Ray H.Hashemi, W.G.B., Jr., Christopher J. Lisanti著,尹建忠译,MRI基础.天津科技翻译出版公司2004年.
[5]J.P.Hornak, "The Basics of MRI," http://www.cis.rit.edu/htbooks/mri.
[6]Ascoli, G.A., Progress and perspectives in computational neuroanatomy. Anatomical Record 1999.257,195-207.
[7]Grenander, U., Miller, M.I., Computational anatomy:An emerging discipline. Quarterly of Applied Mathematics 1998.56,617-694.
[8]Thompson, P.M., Toga, A.W., A framework for computational anatomy. Computing and Visualization in Science 2002.5(1),13-34.
[9]Buckner, R.L., Andrews-Hanna, J.R., Schacter, D.L., The brain's default network-Anatomy, function, and relevance to disease. Year in Cognitive Neuroscience 2008 2008.1124,1-38.
[10]Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America 2001.98,676-682.
[11]Wright, I.C., McGuire, P.K., Poline, J.B., Travere, J.M., Murray, R.M., Frith, C.D., Frackowiak, R.S.J., Friston, K.J., A voxel-based method for the statistical analysis of gray and white matter density applied to schizophrenia. Neuroimage 1995. 2,244-252.
[12]Abell, F., Krams, M., Ashburner, J., Passingham, R., Friston, K., Frackowiak, R., Happe, F., Frith, C, Frith, U., The neuroanatomy of autism:a voxel-based whole brain analysis of structural scans. Neuroreport 1999.10,1647-1651.
[13]Krams, M, Quinton, R., Ashburner, J., Friston, K.J., Frackowiak, R.S.J., Bouloux, P.M.G., Passingham, R.E., Kallmann's syndrome-Mirror movements associated with bilateral corticospinal tract hypertrophy. Neurology 1999.52, 816-822.
[14]May, A., Ashburner, J., Buchel, C, McGonigle, D.J., Friston, K.J., Frackowiak, R.S.J., Goadsby, P.J., Correlation between structural and functional changes in brain in an idiopathic headache syndrome. Nature Medicine 1999.5,836-838.
[15]Shah, P.J., Ebmeier, K.P., Glabus, M.F., Goodwin, G.M., Cortical grey matter reductions associated with treatment-resistant chronic unipolar depression-Controlled magnetic resonance imaging study. British Journal of Psychiatry 1998.172, 527-532.
[16]Sowell, E.R., Thompson, P.M., Holmes, C.J., Batth, R., Jernigan, T.L., Toga, A.W., Localizing age-related changes in brain structure between childhood and adolescence using statistical parametric mapping. Neuroimage 1999.9,587-597.
[17]Vargha-Khadem, F., Watkins, K.E., Price, C.J., Ashburner, J., Alcock, K.J., Connelly, A., Frackowiak, R.S.J., Friston, K.J., Pembrey, M.E., Mishkin, M., Gadian, D.G., Passingham, R.E., Neural basis of an inherited speech and language disorder. Proceedings of the National Academy of Sciences of the United States of America 1998.95,12695-12700.
[18]Woermann, F.G., Free, S.L., Koepp, M.J., Ashburner, J., Duncan, J.S., Voxel-by-voxel comparison of automatically segmented cerebral gray matter-A rater-independent comparison of structural MRI in patients with epilepsy. Neuroimage 1999.10,373-384.
[19]Wright, I.C., Ellison, Z.R., Sharma, T., Friston, K.J., Murray, R.M., McGuire, P.K., Mapping of grey matter changes in schizophrenia. Schizophrenia Research 1999. 35,1-14.
[20]Ashburner, J., Friston, K.J., Voxel-based morphometry-The methods. Neuroimage 2000.11,805-821.
[21]Good, C.D., Johnsrude, I.S., Ashburner, J., Henson, R.N.A., Friston, K.J., Frackowiak, R.S.J., A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 2001.14,21-36.
[22]deLeon, M.J., George, A.E., Golomb, J., Tarshish, C., Convit, A., Kluger, A., DeSanti, S., McRae, T., Ferris, S.H., Reisberg, B., Ince, C., Rusinek, H., Bobinski, M., Quinn, B., Miller, D.C., Wisniewski, H.M., Frequency of hippocampal formation atrophy in normal aging and Alzheimer's disease. Neurobiology of Aging 1997.18, 1-11.
[23]Jack, C.R., Petersen, R.C., Xu, Y.C., Waring, S.C., OBrien, P.C., Tangalos, E.G., Smith, G.E., Ivnik, R.J., Kokmen, E., Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease. Neurology 1997.49,786-794.
[24]Albert, M.S., Cognitive and neurobiologic markers of early Alzheimer disease. Proceedings of the National Academy of Sciences of the United States of America 1996.93,13547-13551.
[25]Boeve, B.F., Maraganore, D.M., Parisi, J.E., Ahlskog, J.E., Graff-Radford, N., Caselli, R.J., Dickson, D.W, Kokmen, E., Petersen, R.C., Pathologic heterogeneity in clinically diagnosed corticobasal degeneration. Neurology 1999.53,795-800.
[26]Double, K.L., Halliday, G.M., Kril, J.J., Harasty, J.A., Cullen, K., Brooks, W.S., Creasey, H., Broe, G.A., Topography of brain atrophy during normal aging and Alzheimer's disease. Neurobiology of Aging 1996.17,513-521.
[27]Frisoni, G.B., Beltramello, A., Weiss, C., Geroldi, C., Bianchetti, A., Trabucchi, M., Linear measures of atrophy in mild Alzheimer disease. American Journal of Neuroradiology 1996.17,913-923.
[28]Grignon, Y., Duyckaerts, C., Bennecib, M., Hauw, J.J., Cytoarchitectonic alterations in the supramarginal gyrus of late onset Alzheimer's disease. Acta Neuropathologica 1998.95,395-406.
[29]Halliday, G.M., McRitchie, D.A., Macdonald, V., Double, K.L., Trent, R.J., McCusker, E., Regional specificity of brain atrophy in Huntington's disease. Experimental Neurology 1998.154,663-672.
[30]Kaye, J.A., Swihart, T., Howieson, D., Dame, A., Moore, M.M., Karnos, T., Camicioli, R., Ball, M., Oken, B., Sexton, G., Volume loss of the hippocampus and temporal lobe in healthy elderly persons destined to develop dementia. Neurology 1997.48,1297-1304.
[31]Kiernan, J.A., Hudson, A.J., Frontal-Lobe Atrophy in Motor-Neuron Diseases. Brain 1994.117,747-757.
[32]Kwon, J.S., McCarley, R.W., Hirayasu, Y., Anderson, J.E., Fischer, I.A., Kikinis, R., Jolesz, F.A., Shenton, M.E., Left planum temporale volume reduction in schizophrenia. Arch Gen Psychiatry 1999.56,142-148.
[33]Pfefferbaum, A., Marsh, L., Structural Brain Imaging in Schizophrenia. Clinical Neuroscience 1995.3,105-111.
[34]Rusinek, H., Deleon, M.J., George, A.E., Stylopoulos, L.A., Chandra, R., Smith, G., Rand, T., Mourino, M., Kowalski, H., Alzheimer-Disease-Measuring Loss of Cerebral Gray-Matter with Mr Imaging. Radiology 1991.178,109-114.
[35]Vonsattel, J.P.G., DiFiglia, M., Huntington disease. Journal of Neuropathology and Experimental Neurology 1998.57,369-384.
[36]Zipursky, R.B., Lambe, E.K., Kapur, S., Mikulis, D.J., Cerebral gray matter volume deficits in first episode psychosis. Archives of General Psychiatry 1998.55, 540-546.
[37]Zipursky, R.B., Lim, K.O., Sullivan, E.V., Brown, B.W., Pfefferbaum, A., Widespread Cerebral Gray-Matter Volume Deficits in Schizophrenia. Archives of General Psychiatry 1992.49,195-205.
[38]Brodmann, K., Vergleichende Lokalisationslehre der Groghirnrinde. Leipzip, Barth 1909.
[39]Von Economo, K., Koskinas, G., Die Cytoarchitektonik der Hirnrinde des erwachsenen Menschen. Julius Springer, Berlin 1925.
[40]Fischl, B., Dale, A.M., Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences of the United States of America 2000.97,11050-11055.
[41]Kim, J.S., Singh, V, Lee, J.K., Lerch, J., Ad-Dab'bagh, Y., MacDonald, D., Lee, J.M., Kim, S.I., Evans, A.C., Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification. Neuroimage 2005.27,210-221.
[42]MacDonald, D., Kabani, N., Avis, D., Evans, A.C., Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI. Neuroimage 2000.12,340-356.
[43]Jones, S.E., Buchbinder, B.R., Aharon, I., Three-dimensional mapping of cortical thickness using Laplace's equation. Human Brain Mapping 2000.11,12-32.
[44]Rocha, K.R., Yezzi, A.J., Prince, J.L., A hybrid Eulerian-Lagrangian approach for thickness, correspondence, and gridding of annular tissues. IEEE Transactions on Image Processing 2007.16,636-648.
[45]Yezzi, A., Prince, J.L., A PDE approach for measuring tissue thickness.2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol 1, Proceedings 2001.87-92.
[46]Yezzi, A., Prince, J.L., A PDE approach for thickness, correspondence, and gridding of annular tissues. Computer Vision-Eccv 2002, Pt Iv 2002.2353,575-589.
[47]Yezzi, A.J., Prince, J.L., An Eulerian PDE approach for computing tissue thickness. IEEE Transactions on Medical Imaging 2003.22,1332-1339.
[48]Johnson L, R.R., Numerical analysis. Reading, MA:Addison-Wesley Publishing Co.1982.
[49]Press WH, T.S., Vetterling WT, Flannery BP, Numerical recipes in C:the art of scientific computing. Cambridge, UK:Cambridge University Press 1992.
[50]Crick, F., Jones, E., Backwardness of Human Neuroanatomy. Nature 1993.361, 109-110.
[51]Penny, W.D., Stephan, K.E., Mechelli, A., Friston, K.J., Comparing dynamic causal models. Neuroimage 2004.22,1157-1172.
[52]Stephan, K.E., Kamper, L., Bozkurt, A., Burns, G.A.P.C., Young, M.P., Kotter, R., Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac). Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 2001.356,1159-1186.
[53]Wright, I.C., Sharma, T., Ellison, Z.R., McGuire, P.K., Friston, K.J., Brammer, M.J., Murray, R.M., Bullmore, E.T., Supra-regional brain systems and the neuropathology of schizophrenia. Cerebral Cortex 1999.9,366-378.
[54]Lerch, J.P., Worsley, K., Shaw, W.P., Greenstein, D.K., Lenroot, R.K., Gledd, J., Evans, A.C., Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI. Neuroimage 2006.31,993-1003.
[55]Andrews, T.J., Halpern, S.D., Purves, D., Correlated size variations in human visual cortex, lateral geniculate nucleus, and optic tract. Journal of Neuroscience 1997. 17,2859-2868.
[56]Bassett, D.S., Bullmore, E., Verchinski, B.A., Mattay, V.S., Weinberger, D.R., Meyer-Lindenberg, A., Hierarchical organization of human cortical networks in health and schizophrenia. Journal of Neuroscience 2008.28,9239-9248.
[57]He, Y., Chen, Z., Evans, A., Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer's Disease. Journal of Neuroscience 2008. 28,4756-4766.
[58]Zilles, K., Armstrong, E., Schleicher, A., Kretschmann, H.J., The Human Pattern of Gyrification in the Cerebral-Cortex. Anatomy and Embryology 1988.179, 173-179.
[59]Schaer, M., Cuadra, M.B., Tamarit, L., Lazeyras, F., Eliez, S., Thiran, J.P., A surface-based approach to quantify local cortical gyrification. IEEE Transactions on Medical Imaging 2008.27,161-170.
[60]沈渔邮,精神病学.人民卫生出版社1995.第三版.
[61]Bench, C.J., Friston, K.J., Brown, R.G., Frackowiak, R.S.J., Dolan, R.J., Regional Cerebral Blood-Flow in Depression Measured by Positron Emission Tomography-the Relationship with Clinical Dimensions. Psychological Medicine 1993.23,579-590.
[62]Bench, C.J., Friston, K.J., Brown, R.G., Scott, L.C., Frackowiak, R.S.J., Dolan, R.J., The Anatomy of Melancholia-Focal Abnormalities of Cerebral Blood-Flow in Major Depression. Psychological Medicine 1992.22,607-615.
[63]Drevets, W.C., Functional anatomical abnormalities in limbic and prefrontal cortical structures in major depression. Cognition, Emotion and Autonomic Responses: The Integrative Role of the Prefrontal Cortex and Limbic Structures 2000.126, 413-431.
[64]Mayberg, H.S., Brannan, S.K., Tekell, J.L., Silva, J.A., Mahurin, R.K., McGinnis, S., Jerabek, P.A., Regional metabolic effects of fluoxetine in major depression:Serial changes and relationship to clinical response. Biological Psychiatry 2000.48, 830-843.
[65]Bremner, J.D., Brain Imaging Handbook. New York:W.W. Norton 2005.
[66]Bremner, J.D., Narayan, M, Anderson, E.R., Staib, L.H., Miller, H.L., Charney, D.S., Hippocampal volume reduction in major depression. American Journal of Psychiatry 2000.157,115-117.
[67]Caetano, S.C., Hatch, J.P., Brambilla, P., Sassi, R.B., Nicoletti, M., Mallinger, A.G., Frank, E., Kupfer, D.J., Keshavan, M.S., Soares, J.C., Anatomical MRI study of hippocampus and amygdala in patients with current and remitted major depression. Psychiatry Research-Neuroimaging 2004.132,141-147.
[68]Frodl, T., Meisenzahl, E.M., Zetzsche, T., Born, C, Groll, C, Jager, M., Leinsinger, G., Bottlender, R., Hahn, K., Moller, H.J., Hippocampal changes in patients with a first episode of major depression. American Journal of Psychiatry 2002. 159,1112-1118.
[69]Hickie, I., Naismith, S., Ward, P.B., Turner, K., Scott, E., Mitchell, P., Wilhelm, K., Parker, G., Reduced hippocampal volumes and memory loss in patients with early-and late-onset depression. British Journal of Psychiatry 2005.186,197-202.
[70]Janssen, J., Pol, H.E.H., Lampe, I.K., Schnack, H.G., de Leeuw, F.E., Kahn, R.S., Heeren, T.J., Hippocampal changes and white matter lesions in early-onset depression. Biological Psychiatry 2004.56,825-831.
[71]Lloyd, A.J., Ferrier, I.N., Barber, R., Gholkar, A., Young, A.H., O'Brien, J.T., Hippocampal volume change in depression:late-and early-onset illness compared. British Journal of Psychiatry 2004.184,488-495.
[72]Hastings, R.S., Parsey, R.V., Oquendo, M.A., Arango, V., Mann, J.J., Volumetric analysis of the prefrontal cortex, amygdala, and hippocampus in major depression. Neuropsychopharmacology 2004.29,952-959.
[73]MacMaster FP, K.V., Hippocampal volume in early onset depression. BMC Med 2004.2,2.
[74]MacQueen, G.M., Campbell, S., McEwen, B.S., MacDonald, K., Amano, S., Joffe, R.T., Nahmias, C., Young, L.T., Course of illness, hippocampal function, and hippocampal volume in major depression. Proceedings of the National Academy of Sciences of the United States of America 2003.100,1387-1392.
[75]Mervaala, E., Fohr, J., Kononen, M., Valkonen-Korhonen, M., Vainio, P., Partanen, K., Partanen, J., Tiihonen, J., Viinamaki, H., Karjalainen, A.K., Lehtonen, J., Quantitative MRI of the hippocampus and amygdala in severe depression. Psychological Medicine 2000.30,117-125.
[76]Neumeister, A., Wood, S., Bonne, O., Nugent, A.C., Luckenbaugh, D.A., Young, T., Bain, E.E., Charney, D.S., Drevets, W.C., Reduced hippocampal volume in unmedicated, remitted patients with major depression versus control subjects. Biological Psychiatry 2005.57,935-937.
[77]Posener, J.A., Wang, L., Price, J.L., Gado, M.H., Province, M.A., Miller, M.I., Babb, C.M., Csernansky, J.G., High-dimensional mapping of the hippocampus in depression. American Journal of Psychiatry 2003.160,83-89.
[78]Sheline, Y.I., Sanghavi, M., Mintun, M.A., Gado, M.H., Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. Journal of Neuroscience 1999.19,5034-5043.
[79]Sheline, Y.I, Wang, P.W., Gado, M.H., Csernansky, J.G., Vannier, M.W., Hippocampal atrophy in recurrent major depression. Proceedings of the National Academy of Sciences of the United States of America 1996.93,3908-3913.
[80]Steffens, D.C., Byrum, C.E., McQuoid, D.R., Greenberg, D.L., Payne, M.E., Blitchington, T.F., MacFall, J.R, Krishnan, K.R.R, Hippocampal volume in geriatric depression. Biological Psychiatry 2000.48,301-309.
[81]Vakili, K., Pillay, S.S., Lafer, B., Fava, M., Renshaw, P.F., Bondello-Cintron, C.M., Yurgelun-Todd, D.A., Hippocampal volume in primary unipolar major depression:A magnetic resonance imaging study. Biological Psychiatry 2000.47, 1087-1090.
[82]Vythilingam, M., Heim, C, Newport, J., Miller, A.H., Anderson, E., Bronen, R., Brummer, M., Staib, L., Vermetten, E., Charney, D.S., Nemeroff, C.B., Bremner, J.D., Childhood trauma associated with smaller hippocampal volume in women with major depression. American Journal of Psychiatry 2002.159,2072-2080.
[83]Rosso, I.M., Cintron, C.M., Steingard, R.J., Renshaw, P.F., Young, A.D., Yurgelun-Todd, D.A., Amygdala and hippocampus volumes in pediatric major depression. Biological Psychiatry 2005.57,21-26.
[84]Rusch, B.D., Abercrombie, H.C., Oakes, T.R., Schaefer, S.M., Davidson, R.J., Hippocampal morphometry in depressed patients and control subjects:Relations to anxiety symptoms. Biological Psychiatry 2001.50,960-964.
[85]von Gunten, A., Fox, N.C., Cipolotti, L., Ron, M.A., A volumetric study of hippocampus and amygdala in depressed patients with subjective memory problems. Journal of Neuropsychiatry and Clinical Neurosciences 2000.12,493-498.
[86]Bremner, J.D., Vythilingam, M., Vermetten, E., Nazeer, A., Adil, J., Khan, S., Staib, L.H., Charney, D.S., Reduced volume of orbitofrontal cortex in major depression. Biological Psychiatry 2002.51,273-279.
[87]Kumar, A., Bilker, W., Lavretsky, H., Gottlieb, G., Volumetric asymmetries in late-onset mood disorders:an attenuation of frontal asymmetry with depression severity. Psychiatry Research-Neuroimaging 2000.100,41-47.
[88]Kumar, A., Jin, Z.S., Bilker, W., Udupa, J., Gottlieb, G., Late-onset minor and major depression:early evidence for common neuroanatomical substrates detected by using MRI. Proceedings of the National Academy of Sciences of the United States of America 1998.95,7654-7658.
[89]Lai, T.J., Payne, M.E., Byrum, C.E., Steffens, D.C., Krishnan, K.R.R., Reduction of orbital frontal cortex volume in geriatric depression. Biological Psychiatry 2000.48, 971-975.
[90]Lee, S.H., Payne, M.E., Steffens, D.C., McQuoid, D.R., Lai, T.J., Provenzale, J.M., Krishnan, K.R.R., Subcortical lesion severity and orbitofrontal cortex volume in geriatric depression. Biological Psychiatry 2003.54,529-533.
[91]Narayan, M., Bremner, J.D., Kumar, A., Neuroanatomic substrates of late-life mental disorders. Journal of Geriatric Psychiatry and Neurology 1999.12,95-106.
[92]Steingard, R.J., Renshaw, P.R., Hennen, J., Lenox, M., Cintron, C.B., Young, A.D., Connor, D.F., Au, T.H., Yurgelun-Todd, D.A., Smaller frontal lobe white matter volumes in depressed adolescents. Biological Psychiatry 2002.52,413-417.
[93]Tebartz van Elst, L., Woermann, F.G., Lemieux, L., Trimble, M.R., Amygdala enlargement in dysthymia—a volumetric study of patients with temporal lobe epilepsy. Biol Psychiatry 1999.46,1614-1623.
[94]Friston, K.J., Holmes, A.P., Worsley, K.J., Poline, J.P., Frith, C.D., J., F.R.S., Statistical parametric maps in functional imaging:A general linear approach. Human Brain Mapping 1995.2,189-210.
[95]Fitzgerald, P.B., Laird, A.R., Maller, J., Daskalakis, Z.J., A meta-analytic study of changes in brain activation in depression. Human Brain Mapping 2008.29,683-695.
[96]Alzheimer, A., Beitrage zur pathologischen anatomie der hirnrinde und zur anatomischen grundlage einiger psychosen. Monatsschrift fur Psychiarie und Neurologie 1897.2,82-120.
[97]Crichton-Browne, J., On the weight of the brain and its components parts in the insane. Brain 1879.2,42-67.
[98]Haug, J.O., Pneumoencephalographic Studies in Mental Disease. Acta Psychiatrica Scandinavica 1962.38,11-104.
[99]Hecker, E., Die hebephrenic. Arch. Patholiche Anat. und fur Physiol. Klinische Medicin 1871.52,394-429.
[100]Jacobi, W., Winkler, H., Encephalographische studien an schizophrenen. Arch. Psychiatrie 1928.84,208-226.
[101]Kahlbaum, K., Die Katatonie oder der Spannungsirresein. Berlin:Hirshwald 1874.
[102]Southard, E.E., A study of the dementia praecox group in the light of certain cases showing anomalies or scleroses in particular brain regions. American Journal of Insanity 1910.67,119-176.
[103]Southard, E.E., On the topographic distribution of cortex lesions and anomalies in dementia praecox with some account of their functional significance. American Journal of Insanity 1915.71,603-671.
[104]Raz, S., Raz, N., Structural Brain Abnormalities in the Major Psychoses-a Quantitative Review of the Evidence from Computerized Imaging. Psychological Bulletin 1990.108,93-108.
[105]Vanhorn, J.D., Mcmanus, I.C., Ventricular Enlargement in Schizophrenia-a Metaanalysis of Studies of the Ventricle-Brain Ratio (Vbr). British Journal of Psychiatry 1992.160,687-697.
[106]Demyer, M.K., Gilmor, R.L., Hendrie, H.C, Demyer, W.E., Augustyn, G.T., Jackson, R.K., Magnetic-Resonance Brain Images in Schizophrenic and Normal Subjects-Influence of Diagnosis and Education. Schizophrenia Bulletin 1988.14, 21-32.
[107]Harvey, I., Ron, M.A., Duboulay, G., Wicks, D., Lewis, S.W., Murray, R.M., Reduction of Cortical Volume in Schizophrenia on Magnetic-Resonance-Imaging. Psychological Medicine 1993.23,591-604.
[108]Raine, A., Lencz, T., Reynolds, G.P., Harrison, G., Sheard, C, Medley, I., Reynolds, L.M., Cooper, J.E., An Evaluation of Structural and Functional Prefrontal Deficits in Schizophrenia-Mri and Neuropsychological Measures. Psychiatry Research-Neuroimaging 1992.45,123-137.
[109]Johnstone, E.C., Owens, D.G.C., Crow, T.J., Frith, C.D., Alexandropolis, K., Bydder, G., Colter, N., Temporal-Lobe Structure as Determined by Nuclear Magnetic-Resonance in Schizophrenia and Bipolar Affective-Disorder. Journal of Neurology Neurosurgery and Psychiatry 1989.52,736-741.
[110]Suddath, R.L., Christison, G.W., Torrey, E.F., Casanova, M.F., Weinberger, D.R., Anatomical Abnormalities in the Brains of Monozygotic Twins Discordant for Schizophrenia. New England Journal of Medicine 1990.322,789-794.
[111]Wright, I.C., Rabe-Hesketh, S., Woodruff, P.W.R., David, A.S., Murray, R.M., Bullmore, E.T., Meta-analysis of regional brain volumes in schizophrenia. American Journal of Psychiatry 2000.157,16-25.
[112]McCarley, R.W., Wible, C.G., Frumin, M., Hirayasu, Y., Levitt, J.J., Fischer, I.A., Shenton, M.E., MRI anatomy of schizophrenia. Biological Psychiatry 1999.45, 1099-1119.
[113]Shenton, M.E., Dickey, C.C., Frumin, M., McCarley, R.W., A review of MRI findings in schizophrenia. Schizophrenia Research 2001.49,1-52.
[114]Chua, S.E., Mckenna, P.J., Schizophrenia-a Brain Disease-a Critical-Review of Structural and Functional Cerebral Abnormality in the Disorder. British Journal of Psychiatry 1995.166,563-582.
[115]Mathew, R.J., Wilson, W.H., Tant, S.R., Robinson, L., Prakash, R., Abnormal Resting Regional Cerebral Blood-Flow Patterns and Their Correlates in Schizophrenia. Archives of General Psychiatry 1988.45,542-549.
[116]Paulman, R.G., Devous, M.D., Gregory, R.R., Herman, J.H., Jennings, L., Bonte, F.J., Nasrallah, H.A., Raese, J.D., Hypofrontality and Cognitive Impairment in Schizophrenia-Dynamic Single-Photon Tomography and Neuropsychological Assessment of Schizophrenic Brain-Function. Biological Psychiatry 1990.27, 377-399.
[117]Wolkin, A., Angrist, B., Wolf, A., Brodie, J.D., Wolkin, B., Jaeger, J., Cancro, R., Rotrosen, J., Low Frontal Glucose-Utilization in Chronic-Schizophrenia-a Replication Study. American Journal of Psychiatry 1988.145,251-253.
[118]Siegel, B.V., Buchsbaum, M.S., Bunney, W.E., Gottschalk, L.A., Haier, R.J., Lohr, J.B., Lottenberg, S., Najafi, A., Nuechterlein, K.H., Potkin, S.G., Wu, J.C., Cortical-Striatal-Thalamic Circuits and Brain Glucose Metabolic-Activity in 70 Unmedicated Male-Schizophrenic Patients. American Journal of Psychiatry 1993.150, 1325-1336.
[119]Andreasen, N.C., Paradiso, S., O'Leary, D.S., "Cognitive dysmetria" as an integrative theory of schizophrenia:A dysfunction in cortical subcortical-cerebellar circuitry? Schizophrenia Bulletin 1998.24,203-218.
[120]Friston, K.J., Frith, C.D., Schizophrenia-a Disconnection Syndrome. Clinical Neuroscience 1995.3,89-97.
[121]Paulus, M.P., Hozack, N.E., Zauscher, B.E., Frank, L., Brown, G.G., McDowell, J., Braff, D.L., Parietal dysfunction is associated with increased outcome-related decision-making in schizophrenia patients. Biological Psychiatry 2002.51,995-1004.
[122]Tan, H.Y., Sust, S., Buckholtz, J.W., Mattay, V.S., Meyer-Lindenberg, A., Egan, M.F., Weinberger, D.R., Callicott, J.H., Dysfunctional prefrontal regional specialization and compensation in schizophrenia. American Journal of Psychiatry 2006.163,1969-1977.
[123]Kim, J.J., Kwon, J.S., Park, H.J., Youn, T., Kang, D.H., Kim, M.S., Lee, D.S., Lee, M.C., Functional disconnection between the prefrontal and parietal cortices during working memory processing in schizophrenia:A [O-15]H2O PET study. American Journal of Psychiatry 2003.160,919-923.
[124]Kim, J.J., Seok, J.H., Park, H.J., Lee, D.S., Lee, M.C., Kwon, J.S., Functional disconnection of the semantic networks in schizophrenia. Neuroreport 2005.16, 355-359.
[125]Spence, S.A., Liddle, P.F., Stefan, M.D., Hellewell, J.S.E., Sharma, T., Friston, K.J., Hirsch, S.R., Frith, C.D., Murray, R.M., Deakin, J.F.W., Grasby, P.M., Functional anatomy of verbal fluency in people with schizophrenia and those at genetic risk-Focal dysfunction and distributed disconnectivity reappraised. British Journal of Psychiatry 2000.176,52-60.
[126]Garrity, A.G., Pearlson, G.D., McKiernan, K., Lloyd, D., Kiehl, K.A., Calhoun, V.D., Aberrant "default mode" functional connectivity in schizophrenia. American Journal of Psychiatry 2007.164,450-457.
[127]Bluhm, R.L., Miller, J., Lanius, R.A., Osuch, E.A., Boksman, K., Neufeld, R.W.J., Theberge, J., Schaefer, B., Williamson, P., Spontaneous low-frequency fluctuations in the BOLD signal in schizophrenic patients:Anomalies in the default network. Schizophrenia Bulletin 2007.33,1004-1012.
[128]Liang, M., Zhou, Y., Jiang, T.Z., Liu, Z.N., Tian, L.X., Liu, H.H., Hao, Y.H., Widespread functional disconnectivity in schizophrenia with resting-state functional magnetic resonance imaging. Neuroreport 2006.17,209-213.
[129]Liu, Y., Liang, M., Zhou, Y., He, Y., Hao, Y.H., Song, M., Yu, C.S., Liu, H.H., Liu, Z.N., Jiang, T.Z., Disrupted small-world networks in schizophrenia. Brain 2008. 131,945-961.
[130]Zhou, Y., Liang, M., Tian, L.X., Wang, K., Hao, Y.H., Liu, H.H., Liu, Z.N., Jiang, T.Z., Functional disintegration in paranoid schizophrenia using resting-state fMRI. Schizophrenia Research 2007.97,194-205.
[131]Mesulam, M.M., From sensation to cognition. Brain 1998.121,1013-1052.
[132]Kay, S.R., Fiszbein, A., Opler, L.A., The Positive and Negative Syndrome Scale (Panss) for Schizophrenia. Schizophrenia Bulletin 1987.13,261-276.
[133]Dale, A.M., Fischl, B., Sereno, M.I., Cortical surface-based analysis-I. Segmentation and surface reconstruction. Neuroimage 1999.9,179-194.
[134]Fischl, B., Sereno, M.I., Dale, A.M., Cortical surface-based analysis-II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 1999.9, 195-207.
[135]Collins, D.L., Neelin, P., Peters, T.M., Evans, A.C., Automatic 3d Intersubject Registration of Mr Volumetric Data in Standardized Talairach Space. Journal of Computer Assisted Tomography 1994.18,192-205.
[136]Talairach, J., Tournoux, P., Co-Planar Stereotaxic Atlas of the Human Brain. New York:Thieme Medical Publishers 1988.
[137]Bollobas, B., Random graphs. London:Academic 1985.
[138]Achard, S., Bullmore, E., Efficiency and cost of economical brain functional networks. Plos Computational Biology 2007.3,174-183.
[139]Latora, V., Marchiori, M., Efficient behavior of small-world networks. Physical Review Letters 2001.8719.
[140]Watts, D.J., Strogatz, S.H., Collective dynamics of'small-world'networks. Nature 1998.393,440-442.
[141]Sporns, O., Honey, C.J., Kotter, R., Identification and Classification of Hubs in Brain Networks. Plos One 2007.2, e1049.
[142]Wasserman, S., Faust, K., Social Network Analysis:Methods and Applications. Cambridge Univ. Press 1994.
[143]Benjamini, Y, Hochberg, Y, Controlling the False Discovery Rate-a Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B-Methodological 1995.57,289-300.
[144]Benjamini, Y, Krieger, A.M., Yekutieli, D., Adaptive linear step-up procedures that control the false discovery rate. Biometrika 2006.93,491-507.
[145]Bullmore, E.T., Suckling, J., Overmeyer, S., Rabe-Hesketh, S., Taylor, E., Brammer, M.J., Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain. IEEE Transactions on Medical Imaging 1999.18,32-42.
[146]He, Y., Chen, Z.J., Evans, A.C., Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cerebral Cortex 2007.17,2407-2419.
[147]Mechelli, A., Friston, K.J., Frackowiak, R.S., Price, C.J., Structural covariance in the human cortex. Journal of Neuroscience 2005.25,8303-8310.
[148]Achard, S., Salvador, R., Whitcher, B., Suckling, J., Bullmore, E., A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. Journal of Neuroscience 2006.26,63-72.
[149]Sporns, O., Chialvo, D.R., Kaiser, M., Hilgetag, C.C., Organization, development and function of complex brain networks. Trends in Cognitive Sciences 2004.8,418-425.
[150]Fransson, P., Spontaneous low-frequency BOLD signal fluctuations:An fMRI investigation of the resting-state default mode of brain function hypothesis. Human Brain Mapping 2005.26,15-29.
[151]Greicius, M.D., Krasnow, B., Reiss, A.L., Menon, V., Functional connectivity in the resting brain:A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences of the United States of America 2003.100, 253-258.
[152]Gusnard, D.A., Raichle, M.E., Searching for a baseline:Functional imaging and the resting human brain. Nature Reviews Neuroscience 2001.2,685-694.
[153]Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., A default mode of brain function. Proc Natl Acad Sci U S A 2001.98, 676-682.
[154]Mason, M.F., Norton, M.I., Van Horn, J.D., Wegner, D.M., Grafton, S.T., Macrae, C.N., Wandering minds:The default network and stimulus-independent thought. Science 2007.315,393-395.
[155]Batchelder, W.H., Riefer, D.M., Multinomial Processing Models of Source Monitoring. Psychological Review 1990.97,548-564.
[156]Frith, C, Functional Imaging and Cognitive Abnormalities. Lancet 1995.346, 615-620.
[157]Neufeld, R.W., On the centrality and significance of stimulus-encoding deficit in schizophrenia. Schizophr Bull 2007.33,982-993.
[158]Weniger, G., Lange, C, Ruther, E., Irle, E., Differential impairments of facial affect recognition in schizophrenia subtypes and major depression. Psychiatry Research 2004.128,135-146.
[159]Weniger, G., Irle, E., Impaired facial affect recognition and emotional changes in subjects with transmodal cortical lesions. Cerebral Cortex 2002.12,258-268.
[160]Pearlson, G.D., Petty, R.G., Ross, C.A., Tien, A.Y., Schizophrenia:A disease of heteromodal association cortex? Neuropsychopharmacology 1996.14,1-17.
[161]Chemerinski, E., Nopoulos, P.C., Crespo-Facorro, B., Andreasen, N.C., Magnotta, V., Morphology of the ventral frontal cortex in schizophrenia:Relationship with social dysfunction. Biological Psychiatry 2002.52,1-8.
[162]Crespo-Facorro, B., Kim, J.J., Andreasen, N.C., O'Leary, D.S., Bockholt, H.J., Magnotta, V., Insular cortex abnormalities in schizophrenia:a structural magnetic resonance imaging study of first-episode patients. Schizophrenia Research 2000.46, 35-43.
[163]Hempel, A., Hempel, E., Schonknecht, P., Stippich, C., Schroder, J., Impairment in basal limbic function in schizophrenia during affect recognition. Psychiatry Research-Neuroimaging 2003.122,115-124.
[164]Sigmundsson, T., Suckling, J., Maier, M., Williams, S.C.R., Bullmore, E.T., Greenwood, K.E., Fukuda, R., Ron, M.A., Toone, B.K., Structural abnormalities in frontal, temporal, and limbic regions and interconnecting white matter tracts in schizophrenic patients with prominent negative symptoms. American Journal of Psychiatry 2001.158,234-243.
[165]Streit, M., Ioannides, A., Sinnemann, T., Wolwer, W., Dammers, J., Zilles, K., Gaebel, W., Disturbed facial affect recognition in patients with schizophrenia associated with hypoactivity in distributed brain regions:A magnetoencephalographic study. American Journal of Psychiatry 2001.158,1429-1436.
[166]Olabarriaga, S.D., Smeulders, A.W., Interaction in the segmentation of medical images:a survey. Medical Image Analysis 2001.5,127-142.
[167]Pham, D.L., Xu, C.Y., Prince, J.L., Current methods in medical image segmentation. Annual Review of Biomedical Engineering 2000.2,315-337.
[168]Sahoo, P.K., Soltani, S., Wong, A.K.C., Chen, Y.C., A Survey of Thresholding Techniques. Computer Vision Graphics and Image Processing 1988.41,233-260.
[169]Prewitt, J.M.S., Object enhancement and extraction. Picture processing and Psychopictorics 1970. in B.S. Lipkin and A. Rosenfeld (Eds.), Academic Press.
[170]Canny, J., A Computational Approach to Edge-Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 1986.8,679-698.
[171]Schnack, H.G., Pol, H.E.H, Baare, W.F.C., Viergever, M.A., Kahn, R.S., Automatic segmentation of the ventricular system from MR images of the human brain. Neuroimage 2001.14,95-104.
[172]Tang, H., Wu, E.X., Ma, Q.Y, Gallagher, D., Perera, G.M., Zhuang, T., MRI brain image segmentation by multi-resolution edge detection and region selection. Computerized Medical Imaging and Graphics 2000.24,349-357.
[173]Zhu, S.C., Yuille, A., Region competition:Unifying snakes, region growing, and Bayes/MDL for multiband image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 1996.18,884-900.
[174]Clarke, L.P., Velthuizen, R.P., Camacho, M.A., Heine, J.J., Vaidyanathan, M., Hall, L.O., Thatcher, R.W., Silbiger, M.L., Mri Segmentation-Methods and Applications. Magnetic Resonance Imaging 1995.13,343-368.
[175]Withey, D.J., Koles, Z.J., Medical image segmentation:Methods and software. 2007 Joint Meeting of the 6th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging 2007.143-146.
[176]Pina, R.K., Puetter, R.C., Bayesian Image-Reconstruction-the Pixon and Optimal Image Modeling. Publications of the Astronomical Society of the Pacific 1993.105,630-637.
[177]Descombes, X., Kruggel, F., A Markov pixon information approach for low-level image description. IEEE Transactions on Pattern Analysis and Machine Intelligence 1999.21,482-494.
[178]Lin, L., Zhu, L.T., Yang, F.G., Jiang, T.Z., A novel pixon-representation for image segmentation based on Markov random field. Image and Vision Computing 2008.26,1507-1514.
[179]Yang, F.G., Jiang, T.Z., Pixon-based image segmentation with Markov random fields. IEEE Transactions on Image Processing 2003.12,1552-1559.
[180]Fukunaga, K., Hostetler, L.D., Estimation of Gradient of a Density-Function, with Applications in Pattern-Recognition. IEEE Transactions on Information Theory 1975. It21,32-40.
[181]Jimenez-Alaniz, J.R., Medina-Banuelos, V., Yanez-Suarez, O., Data-driven brain MRI segmentation supported on edge confidence and A priori tissue information. IEEE Transactions on Medical Imaging 2006.25,74-83.
[182]Cheng, Y.Z., Mean Shift, Mode Seeking, and Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 1995.17,790-799.
[183]Comaniciu, D., Meer, P., Mean shift:A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 2002.24, 603-619.
[184]Comaniciu, D., Ramesh, V, Meer, P., The variable bandwidth mean shift and data-driven scale selection. Eighth IEEE International Conference on Computer Vision, Vol I, Proceedings 2001.438-445.
[185]Wells, W.M., Grimson, W.E.L., Kikinis, R., Jolesz, F.A., Adaptive segmentation of MRI data. IEEE Transactions on Medical Imaging 1996.15,429-442.
[186]Besag, J., On the Statistical-Analysis of Dirty Pictures. Journal of the Royal Statistical Society Series B-Methodological 1986.48,259-302.
[187]Andrey, P., Tarroux, P., Unsupervised segmentation of Markov random field modeled textured images using selectionist relaxation. Ieee Transactions on Pattern Analysis and Machine Intelligence 1998.20,252-262.
[188]Held, K., Kops, E.R., Krause, B.J., Wells, W.M., Kikinis, R., Muller-Gartner, H.W., Markov random field segmentation of brain MR images. IEEE Transactions on Medical Imaging 1997.16,878-886.
[189]Kato, Z., Zerubia, J., Berthod, M., Unsupervised parallel image classification using Markovian models. Pattern Recognition 1999.32,591-604.
[190]Kwan, R.K.S., Evans, A.C., Pike, G.B., MRI simulation-based evaluation of image-processing and classification methods. IEEE Transactions on Medical Imaging 1999.18,1085-1097.
[191]Cocosco, C.A., Kollokian, V., Kwan, R.K.S., Evans, A.C., Brainweb:online interface to a 3D MRI simulated brain database. Neuroimage 1997.5, S425.
[192]Hasanzadeh, M., Kasaei, S., Fuzzy Image Segmentation Using Membership Connectedness. Eurasip Journal on Advances in Signal Processing 2008.
[193]Zhou, Y.X., Bai, J., Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI. IEEE Transactions on Biomedical Engineering 2007.54,122-129.
[194]Ibrahim, M., John, N., Kabuka, M., Younis, A., Hidden Markov models-based 3D MRI brain segmentation. Image and Vision Computing 2006.24,1065-1079.
[195]Rivera, M., Ocegueda, O., Marroquin, J.L., Entropy-controlled quadratic Markov measure field models for efficient image segmentation. IEEE Transactions on Image Processing 2007.16,3047-3057.
[196]Solomon, J., Butman, J.A., Sood, A., Segmentation of brain tumors in 4D MR images using the hidden Markov model. Computer Methods and Programs in Biomedicine 2006.84,76-85.
[197]Shattuck, D.W., Sandor-Leahy, S.R., Schaper, K.A., Rottenberg, D.A., Leahy, R.M., Magnetic resonance image tissue classification using a partial volume model. Neuroimage 2001.13,856-876.
[198]Siyal, M.Y., Yu, L., An intelligent modified fuzzy c-means based algorithm for bias estimation and segmentation of brain MRI. Pattern Recognition Letters 2005.26, 2052-2062.
[2]孙久荣,脑科学导论.北京大学出版社2001年.
[3]李振平,临床中枢神经解剖学.北京科学出版社2003年.
[4]Ray H.Hashemi, W.G.B., Jr., Christopher J. Lisanti著,尹建忠译,MRI基础.天津科技翻译出版公司2004年.
[5]J.P.Hornak, "The Basics of MRI," http://www.cis.rit.edu/htbooks/mri.
[6]Ascoli, G.A., Progress and perspectives in computational neuroanatomy. Anatomical Record 1999.257,195-207.
[7]Grenander, U., Miller, M.I., Computational anatomy:An emerging discipline. Quarterly of Applied Mathematics 1998.56,617-694.
[8]Thompson, P.M., Toga, A.W., A framework for computational anatomy. Computing and Visualization in Science 2002.5(1),13-34.
[9]Buckner, R.L., Andrews-Hanna, J.R., Schacter, D.L., The brain's default network-Anatomy, function, and relevance to disease. Year in Cognitive Neuroscience 2008 2008.1124,1-38.
[10]Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America 2001.98,676-682.
[11]Wright, I.C., McGuire, P.K., Poline, J.B., Travere, J.M., Murray, R.M., Frith, C.D., Frackowiak, R.S.J., Friston, K.J., A voxel-based method for the statistical analysis of gray and white matter density applied to schizophrenia. Neuroimage 1995. 2,244-252.
[12]Abell, F., Krams, M., Ashburner, J., Passingham, R., Friston, K., Frackowiak, R., Happe, F., Frith, C, Frith, U., The neuroanatomy of autism:a voxel-based whole brain analysis of structural scans. Neuroreport 1999.10,1647-1651.
[13]Krams, M, Quinton, R., Ashburner, J., Friston, K.J., Frackowiak, R.S.J., Bouloux, P.M.G., Passingham, R.E., Kallmann's syndrome-Mirror movements associated with bilateral corticospinal tract hypertrophy. Neurology 1999.52, 816-822.
[14]May, A., Ashburner, J., Buchel, C, McGonigle, D.J., Friston, K.J., Frackowiak, R.S.J., Goadsby, P.J., Correlation between structural and functional changes in brain in an idiopathic headache syndrome. Nature Medicine 1999.5,836-838.
[15]Shah, P.J., Ebmeier, K.P., Glabus, M.F., Goodwin, G.M., Cortical grey matter reductions associated with treatment-resistant chronic unipolar depression-Controlled magnetic resonance imaging study. British Journal of Psychiatry 1998.172, 527-532.
[16]Sowell, E.R., Thompson, P.M., Holmes, C.J., Batth, R., Jernigan, T.L., Toga, A.W., Localizing age-related changes in brain structure between childhood and adolescence using statistical parametric mapping. Neuroimage 1999.9,587-597.
[17]Vargha-Khadem, F., Watkins, K.E., Price, C.J., Ashburner, J., Alcock, K.J., Connelly, A., Frackowiak, R.S.J., Friston, K.J., Pembrey, M.E., Mishkin, M., Gadian, D.G., Passingham, R.E., Neural basis of an inherited speech and language disorder. Proceedings of the National Academy of Sciences of the United States of America 1998.95,12695-12700.
[18]Woermann, F.G., Free, S.L., Koepp, M.J., Ashburner, J., Duncan, J.S., Voxel-by-voxel comparison of automatically segmented cerebral gray matter-A rater-independent comparison of structural MRI in patients with epilepsy. Neuroimage 1999.10,373-384.
[19]Wright, I.C., Ellison, Z.R., Sharma, T., Friston, K.J., Murray, R.M., McGuire, P.K., Mapping of grey matter changes in schizophrenia. Schizophrenia Research 1999. 35,1-14.
[20]Ashburner, J., Friston, K.J., Voxel-based morphometry-The methods. Neuroimage 2000.11,805-821.
[21]Good, C.D., Johnsrude, I.S., Ashburner, J., Henson, R.N.A., Friston, K.J., Frackowiak, R.S.J., A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 2001.14,21-36.
[22]deLeon, M.J., George, A.E., Golomb, J., Tarshish, C., Convit, A., Kluger, A., DeSanti, S., McRae, T., Ferris, S.H., Reisberg, B., Ince, C., Rusinek, H., Bobinski, M., Quinn, B., Miller, D.C., Wisniewski, H.M., Frequency of hippocampal formation atrophy in normal aging and Alzheimer's disease. Neurobiology of Aging 1997.18, 1-11.
[23]Jack, C.R., Petersen, R.C., Xu, Y.C., Waring, S.C., OBrien, P.C., Tangalos, E.G., Smith, G.E., Ivnik, R.J., Kokmen, E., Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease. Neurology 1997.49,786-794.
[24]Albert, M.S., Cognitive and neurobiologic markers of early Alzheimer disease. Proceedings of the National Academy of Sciences of the United States of America 1996.93,13547-13551.
[25]Boeve, B.F., Maraganore, D.M., Parisi, J.E., Ahlskog, J.E., Graff-Radford, N., Caselli, R.J., Dickson, D.W, Kokmen, E., Petersen, R.C., Pathologic heterogeneity in clinically diagnosed corticobasal degeneration. Neurology 1999.53,795-800.
[26]Double, K.L., Halliday, G.M., Kril, J.J., Harasty, J.A., Cullen, K., Brooks, W.S., Creasey, H., Broe, G.A., Topography of brain atrophy during normal aging and Alzheimer's disease. Neurobiology of Aging 1996.17,513-521.
[27]Frisoni, G.B., Beltramello, A., Weiss, C., Geroldi, C., Bianchetti, A., Trabucchi, M., Linear measures of atrophy in mild Alzheimer disease. American Journal of Neuroradiology 1996.17,913-923.
[28]Grignon, Y., Duyckaerts, C., Bennecib, M., Hauw, J.J., Cytoarchitectonic alterations in the supramarginal gyrus of late onset Alzheimer's disease. Acta Neuropathologica 1998.95,395-406.
[29]Halliday, G.M., McRitchie, D.A., Macdonald, V., Double, K.L., Trent, R.J., McCusker, E., Regional specificity of brain atrophy in Huntington's disease. Experimental Neurology 1998.154,663-672.
[30]Kaye, J.A., Swihart, T., Howieson, D., Dame, A., Moore, M.M., Karnos, T., Camicioli, R., Ball, M., Oken, B., Sexton, G., Volume loss of the hippocampus and temporal lobe in healthy elderly persons destined to develop dementia. Neurology 1997.48,1297-1304.
[31]Kiernan, J.A., Hudson, A.J., Frontal-Lobe Atrophy in Motor-Neuron Diseases. Brain 1994.117,747-757.
[32]Kwon, J.S., McCarley, R.W., Hirayasu, Y., Anderson, J.E., Fischer, I.A., Kikinis, R., Jolesz, F.A., Shenton, M.E., Left planum temporale volume reduction in schizophrenia. Arch Gen Psychiatry 1999.56,142-148.
[33]Pfefferbaum, A., Marsh, L., Structural Brain Imaging in Schizophrenia. Clinical Neuroscience 1995.3,105-111.
[34]Rusinek, H., Deleon, M.J., George, A.E., Stylopoulos, L.A., Chandra, R., Smith, G., Rand, T., Mourino, M., Kowalski, H., Alzheimer-Disease-Measuring Loss of Cerebral Gray-Matter with Mr Imaging. Radiology 1991.178,109-114.
[35]Vonsattel, J.P.G., DiFiglia, M., Huntington disease. Journal of Neuropathology and Experimental Neurology 1998.57,369-384.
[36]Zipursky, R.B., Lambe, E.K., Kapur, S., Mikulis, D.J., Cerebral gray matter volume deficits in first episode psychosis. Archives of General Psychiatry 1998.55, 540-546.
[37]Zipursky, R.B., Lim, K.O., Sullivan, E.V., Brown, B.W., Pfefferbaum, A., Widespread Cerebral Gray-Matter Volume Deficits in Schizophrenia. Archives of General Psychiatry 1992.49,195-205.
[38]Brodmann, K., Vergleichende Lokalisationslehre der Groghirnrinde. Leipzip, Barth 1909.
[39]Von Economo, K., Koskinas, G., Die Cytoarchitektonik der Hirnrinde des erwachsenen Menschen. Julius Springer, Berlin 1925.
[40]Fischl, B., Dale, A.M., Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences of the United States of America 2000.97,11050-11055.
[41]Kim, J.S., Singh, V, Lee, J.K., Lerch, J., Ad-Dab'bagh, Y., MacDonald, D., Lee, J.M., Kim, S.I., Evans, A.C., Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification. Neuroimage 2005.27,210-221.
[42]MacDonald, D., Kabani, N., Avis, D., Evans, A.C., Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI. Neuroimage 2000.12,340-356.
[43]Jones, S.E., Buchbinder, B.R., Aharon, I., Three-dimensional mapping of cortical thickness using Laplace's equation. Human Brain Mapping 2000.11,12-32.
[44]Rocha, K.R., Yezzi, A.J., Prince, J.L., A hybrid Eulerian-Lagrangian approach for thickness, correspondence, and gridding of annular tissues. IEEE Transactions on Image Processing 2007.16,636-648.
[45]Yezzi, A., Prince, J.L., A PDE approach for measuring tissue thickness.2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol 1, Proceedings 2001.87-92.
[46]Yezzi, A., Prince, J.L., A PDE approach for thickness, correspondence, and gridding of annular tissues. Computer Vision-Eccv 2002, Pt Iv 2002.2353,575-589.
[47]Yezzi, A.J., Prince, J.L., An Eulerian PDE approach for computing tissue thickness. IEEE Transactions on Medical Imaging 2003.22,1332-1339.
[48]Johnson L, R.R., Numerical analysis. Reading, MA:Addison-Wesley Publishing Co.1982.
[49]Press WH, T.S., Vetterling WT, Flannery BP, Numerical recipes in C:the art of scientific computing. Cambridge, UK:Cambridge University Press 1992.
[50]Crick, F., Jones, E., Backwardness of Human Neuroanatomy. Nature 1993.361, 109-110.
[51]Penny, W.D., Stephan, K.E., Mechelli, A., Friston, K.J., Comparing dynamic causal models. Neuroimage 2004.22,1157-1172.
[52]Stephan, K.E., Kamper, L., Bozkurt, A., Burns, G.A.P.C., Young, M.P., Kotter, R., Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac). Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 2001.356,1159-1186.
[53]Wright, I.C., Sharma, T., Ellison, Z.R., McGuire, P.K., Friston, K.J., Brammer, M.J., Murray, R.M., Bullmore, E.T., Supra-regional brain systems and the neuropathology of schizophrenia. Cerebral Cortex 1999.9,366-378.
[54]Lerch, J.P., Worsley, K., Shaw, W.P., Greenstein, D.K., Lenroot, R.K., Gledd, J., Evans, A.C., Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI. Neuroimage 2006.31,993-1003.
[55]Andrews, T.J., Halpern, S.D., Purves, D., Correlated size variations in human visual cortex, lateral geniculate nucleus, and optic tract. Journal of Neuroscience 1997. 17,2859-2868.
[56]Bassett, D.S., Bullmore, E., Verchinski, B.A., Mattay, V.S., Weinberger, D.R., Meyer-Lindenberg, A., Hierarchical organization of human cortical networks in health and schizophrenia. Journal of Neuroscience 2008.28,9239-9248.
[57]He, Y., Chen, Z., Evans, A., Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer's Disease. Journal of Neuroscience 2008. 28,4756-4766.
[58]Zilles, K., Armstrong, E., Schleicher, A., Kretschmann, H.J., The Human Pattern of Gyrification in the Cerebral-Cortex. Anatomy and Embryology 1988.179, 173-179.
[59]Schaer, M., Cuadra, M.B., Tamarit, L., Lazeyras, F., Eliez, S., Thiran, J.P., A surface-based approach to quantify local cortical gyrification. IEEE Transactions on Medical Imaging 2008.27,161-170.
[60]沈渔邮,精神病学.人民卫生出版社1995.第三版.
[61]Bench, C.J., Friston, K.J., Brown, R.G., Frackowiak, R.S.J., Dolan, R.J., Regional Cerebral Blood-Flow in Depression Measured by Positron Emission Tomography-the Relationship with Clinical Dimensions. Psychological Medicine 1993.23,579-590.
[62]Bench, C.J., Friston, K.J., Brown, R.G., Scott, L.C., Frackowiak, R.S.J., Dolan, R.J., The Anatomy of Melancholia-Focal Abnormalities of Cerebral Blood-Flow in Major Depression. Psychological Medicine 1992.22,607-615.
[63]Drevets, W.C., Functional anatomical abnormalities in limbic and prefrontal cortical structures in major depression. Cognition, Emotion and Autonomic Responses: The Integrative Role of the Prefrontal Cortex and Limbic Structures 2000.126, 413-431.
[64]Mayberg, H.S., Brannan, S.K., Tekell, J.L., Silva, J.A., Mahurin, R.K., McGinnis, S., Jerabek, P.A., Regional metabolic effects of fluoxetine in major depression:Serial changes and relationship to clinical response. Biological Psychiatry 2000.48, 830-843.
[65]Bremner, J.D., Brain Imaging Handbook. New York:W.W. Norton 2005.
[66]Bremner, J.D., Narayan, M, Anderson, E.R., Staib, L.H., Miller, H.L., Charney, D.S., Hippocampal volume reduction in major depression. American Journal of Psychiatry 2000.157,115-117.
[67]Caetano, S.C., Hatch, J.P., Brambilla, P., Sassi, R.B., Nicoletti, M., Mallinger, A.G., Frank, E., Kupfer, D.J., Keshavan, M.S., Soares, J.C., Anatomical MRI study of hippocampus and amygdala in patients with current and remitted major depression. Psychiatry Research-Neuroimaging 2004.132,141-147.
[68]Frodl, T., Meisenzahl, E.M., Zetzsche, T., Born, C, Groll, C, Jager, M., Leinsinger, G., Bottlender, R., Hahn, K., Moller, H.J., Hippocampal changes in patients with a first episode of major depression. American Journal of Psychiatry 2002. 159,1112-1118.
[69]Hickie, I., Naismith, S., Ward, P.B., Turner, K., Scott, E., Mitchell, P., Wilhelm, K., Parker, G., Reduced hippocampal volumes and memory loss in patients with early-and late-onset depression. British Journal of Psychiatry 2005.186,197-202.
[70]Janssen, J., Pol, H.E.H., Lampe, I.K., Schnack, H.G., de Leeuw, F.E., Kahn, R.S., Heeren, T.J., Hippocampal changes and white matter lesions in early-onset depression. Biological Psychiatry 2004.56,825-831.
[71]Lloyd, A.J., Ferrier, I.N., Barber, R., Gholkar, A., Young, A.H., O'Brien, J.T., Hippocampal volume change in depression:late-and early-onset illness compared. British Journal of Psychiatry 2004.184,488-495.
[72]Hastings, R.S., Parsey, R.V., Oquendo, M.A., Arango, V., Mann, J.J., Volumetric analysis of the prefrontal cortex, amygdala, and hippocampus in major depression. Neuropsychopharmacology 2004.29,952-959.
[73]MacMaster FP, K.V., Hippocampal volume in early onset depression. BMC Med 2004.2,2.
[74]MacQueen, G.M., Campbell, S., McEwen, B.S., MacDonald, K., Amano, S., Joffe, R.T., Nahmias, C., Young, L.T., Course of illness, hippocampal function, and hippocampal volume in major depression. Proceedings of the National Academy of Sciences of the United States of America 2003.100,1387-1392.
[75]Mervaala, E., Fohr, J., Kononen, M., Valkonen-Korhonen, M., Vainio, P., Partanen, K., Partanen, J., Tiihonen, J., Viinamaki, H., Karjalainen, A.K., Lehtonen, J., Quantitative MRI of the hippocampus and amygdala in severe depression. Psychological Medicine 2000.30,117-125.
[76]Neumeister, A., Wood, S., Bonne, O., Nugent, A.C., Luckenbaugh, D.A., Young, T., Bain, E.E., Charney, D.S., Drevets, W.C., Reduced hippocampal volume in unmedicated, remitted patients with major depression versus control subjects. Biological Psychiatry 2005.57,935-937.
[77]Posener, J.A., Wang, L., Price, J.L., Gado, M.H., Province, M.A., Miller, M.I., Babb, C.M., Csernansky, J.G., High-dimensional mapping of the hippocampus in depression. American Journal of Psychiatry 2003.160,83-89.
[78]Sheline, Y.I., Sanghavi, M., Mintun, M.A., Gado, M.H., Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. Journal of Neuroscience 1999.19,5034-5043.
[79]Sheline, Y.I, Wang, P.W., Gado, M.H., Csernansky, J.G., Vannier, M.W., Hippocampal atrophy in recurrent major depression. Proceedings of the National Academy of Sciences of the United States of America 1996.93,3908-3913.
[80]Steffens, D.C., Byrum, C.E., McQuoid, D.R., Greenberg, D.L., Payne, M.E., Blitchington, T.F., MacFall, J.R, Krishnan, K.R.R, Hippocampal volume in geriatric depression. Biological Psychiatry 2000.48,301-309.
[81]Vakili, K., Pillay, S.S., Lafer, B., Fava, M., Renshaw, P.F., Bondello-Cintron, C.M., Yurgelun-Todd, D.A., Hippocampal volume in primary unipolar major depression:A magnetic resonance imaging study. Biological Psychiatry 2000.47, 1087-1090.
[82]Vythilingam, M., Heim, C, Newport, J., Miller, A.H., Anderson, E., Bronen, R., Brummer, M., Staib, L., Vermetten, E., Charney, D.S., Nemeroff, C.B., Bremner, J.D., Childhood trauma associated with smaller hippocampal volume in women with major depression. American Journal of Psychiatry 2002.159,2072-2080.
[83]Rosso, I.M., Cintron, C.M., Steingard, R.J., Renshaw, P.F., Young, A.D., Yurgelun-Todd, D.A., Amygdala and hippocampus volumes in pediatric major depression. Biological Psychiatry 2005.57,21-26.
[84]Rusch, B.D., Abercrombie, H.C., Oakes, T.R., Schaefer, S.M., Davidson, R.J., Hippocampal morphometry in depressed patients and control subjects:Relations to anxiety symptoms. Biological Psychiatry 2001.50,960-964.
[85]von Gunten, A., Fox, N.C., Cipolotti, L., Ron, M.A., A volumetric study of hippocampus and amygdala in depressed patients with subjective memory problems. Journal of Neuropsychiatry and Clinical Neurosciences 2000.12,493-498.
[86]Bremner, J.D., Vythilingam, M., Vermetten, E., Nazeer, A., Adil, J., Khan, S., Staib, L.H., Charney, D.S., Reduced volume of orbitofrontal cortex in major depression. Biological Psychiatry 2002.51,273-279.
[87]Kumar, A., Bilker, W., Lavretsky, H., Gottlieb, G., Volumetric asymmetries in late-onset mood disorders:an attenuation of frontal asymmetry with depression severity. Psychiatry Research-Neuroimaging 2000.100,41-47.
[88]Kumar, A., Jin, Z.S., Bilker, W., Udupa, J., Gottlieb, G., Late-onset minor and major depression:early evidence for common neuroanatomical substrates detected by using MRI. Proceedings of the National Academy of Sciences of the United States of America 1998.95,7654-7658.
[89]Lai, T.J., Payne, M.E., Byrum, C.E., Steffens, D.C., Krishnan, K.R.R., Reduction of orbital frontal cortex volume in geriatric depression. Biological Psychiatry 2000.48, 971-975.
[90]Lee, S.H., Payne, M.E., Steffens, D.C., McQuoid, D.R., Lai, T.J., Provenzale, J.M., Krishnan, K.R.R., Subcortical lesion severity and orbitofrontal cortex volume in geriatric depression. Biological Psychiatry 2003.54,529-533.
[91]Narayan, M., Bremner, J.D., Kumar, A., Neuroanatomic substrates of late-life mental disorders. Journal of Geriatric Psychiatry and Neurology 1999.12,95-106.
[92]Steingard, R.J., Renshaw, P.R., Hennen, J., Lenox, M., Cintron, C.B., Young, A.D., Connor, D.F., Au, T.H., Yurgelun-Todd, D.A., Smaller frontal lobe white matter volumes in depressed adolescents. Biological Psychiatry 2002.52,413-417.
[93]Tebartz van Elst, L., Woermann, F.G., Lemieux, L., Trimble, M.R., Amygdala enlargement in dysthymia—a volumetric study of patients with temporal lobe epilepsy. Biol Psychiatry 1999.46,1614-1623.
[94]Friston, K.J., Holmes, A.P., Worsley, K.J., Poline, J.P., Frith, C.D., J., F.R.S., Statistical parametric maps in functional imaging:A general linear approach. Human Brain Mapping 1995.2,189-210.
[95]Fitzgerald, P.B., Laird, A.R., Maller, J., Daskalakis, Z.J., A meta-analytic study of changes in brain activation in depression. Human Brain Mapping 2008.29,683-695.
[96]Alzheimer, A., Beitrage zur pathologischen anatomie der hirnrinde und zur anatomischen grundlage einiger psychosen. Monatsschrift fur Psychiarie und Neurologie 1897.2,82-120.
[97]Crichton-Browne, J., On the weight of the brain and its components parts in the insane. Brain 1879.2,42-67.
[98]Haug, J.O., Pneumoencephalographic Studies in Mental Disease. Acta Psychiatrica Scandinavica 1962.38,11-104.
[99]Hecker, E., Die hebephrenic. Arch. Patholiche Anat. und fur Physiol. Klinische Medicin 1871.52,394-429.
[100]Jacobi, W., Winkler, H., Encephalographische studien an schizophrenen. Arch. Psychiatrie 1928.84,208-226.
[101]Kahlbaum, K., Die Katatonie oder der Spannungsirresein. Berlin:Hirshwald 1874.
[102]Southard, E.E., A study of the dementia praecox group in the light of certain cases showing anomalies or scleroses in particular brain regions. American Journal of Insanity 1910.67,119-176.
[103]Southard, E.E., On the topographic distribution of cortex lesions and anomalies in dementia praecox with some account of their functional significance. American Journal of Insanity 1915.71,603-671.
[104]Raz, S., Raz, N., Structural Brain Abnormalities in the Major Psychoses-a Quantitative Review of the Evidence from Computerized Imaging. Psychological Bulletin 1990.108,93-108.
[105]Vanhorn, J.D., Mcmanus, I.C., Ventricular Enlargement in Schizophrenia-a Metaanalysis of Studies of the Ventricle-Brain Ratio (Vbr). British Journal of Psychiatry 1992.160,687-697.
[106]Demyer, M.K., Gilmor, R.L., Hendrie, H.C, Demyer, W.E., Augustyn, G.T., Jackson, R.K., Magnetic-Resonance Brain Images in Schizophrenic and Normal Subjects-Influence of Diagnosis and Education. Schizophrenia Bulletin 1988.14, 21-32.
[107]Harvey, I., Ron, M.A., Duboulay, G., Wicks, D., Lewis, S.W., Murray, R.M., Reduction of Cortical Volume in Schizophrenia on Magnetic-Resonance-Imaging. Psychological Medicine 1993.23,591-604.
[108]Raine, A., Lencz, T., Reynolds, G.P., Harrison, G., Sheard, C, Medley, I., Reynolds, L.M., Cooper, J.E., An Evaluation of Structural and Functional Prefrontal Deficits in Schizophrenia-Mri and Neuropsychological Measures. Psychiatry Research-Neuroimaging 1992.45,123-137.
[109]Johnstone, E.C., Owens, D.G.C., Crow, T.J., Frith, C.D., Alexandropolis, K., Bydder, G., Colter, N., Temporal-Lobe Structure as Determined by Nuclear Magnetic-Resonance in Schizophrenia and Bipolar Affective-Disorder. Journal of Neurology Neurosurgery and Psychiatry 1989.52,736-741.
[110]Suddath, R.L., Christison, G.W., Torrey, E.F., Casanova, M.F., Weinberger, D.R., Anatomical Abnormalities in the Brains of Monozygotic Twins Discordant for Schizophrenia. New England Journal of Medicine 1990.322,789-794.
[111]Wright, I.C., Rabe-Hesketh, S., Woodruff, P.W.R., David, A.S., Murray, R.M., Bullmore, E.T., Meta-analysis of regional brain volumes in schizophrenia. American Journal of Psychiatry 2000.157,16-25.
[112]McCarley, R.W., Wible, C.G., Frumin, M., Hirayasu, Y., Levitt, J.J., Fischer, I.A., Shenton, M.E., MRI anatomy of schizophrenia. Biological Psychiatry 1999.45, 1099-1119.
[113]Shenton, M.E., Dickey, C.C., Frumin, M., McCarley, R.W., A review of MRI findings in schizophrenia. Schizophrenia Research 2001.49,1-52.
[114]Chua, S.E., Mckenna, P.J., Schizophrenia-a Brain Disease-a Critical-Review of Structural and Functional Cerebral Abnormality in the Disorder. British Journal of Psychiatry 1995.166,563-582.
[115]Mathew, R.J., Wilson, W.H., Tant, S.R., Robinson, L., Prakash, R., Abnormal Resting Regional Cerebral Blood-Flow Patterns and Their Correlates in Schizophrenia. Archives of General Psychiatry 1988.45,542-549.
[116]Paulman, R.G., Devous, M.D., Gregory, R.R., Herman, J.H., Jennings, L., Bonte, F.J., Nasrallah, H.A., Raese, J.D., Hypofrontality and Cognitive Impairment in Schizophrenia-Dynamic Single-Photon Tomography and Neuropsychological Assessment of Schizophrenic Brain-Function. Biological Psychiatry 1990.27, 377-399.
[117]Wolkin, A., Angrist, B., Wolf, A., Brodie, J.D., Wolkin, B., Jaeger, J., Cancro, R., Rotrosen, J., Low Frontal Glucose-Utilization in Chronic-Schizophrenia-a Replication Study. American Journal of Psychiatry 1988.145,251-253.
[118]Siegel, B.V., Buchsbaum, M.S., Bunney, W.E., Gottschalk, L.A., Haier, R.J., Lohr, J.B., Lottenberg, S., Najafi, A., Nuechterlein, K.H., Potkin, S.G., Wu, J.C., Cortical-Striatal-Thalamic Circuits and Brain Glucose Metabolic-Activity in 70 Unmedicated Male-Schizophrenic Patients. American Journal of Psychiatry 1993.150, 1325-1336.
[119]Andreasen, N.C., Paradiso, S., O'Leary, D.S., "Cognitive dysmetria" as an integrative theory of schizophrenia:A dysfunction in cortical subcortical-cerebellar circuitry? Schizophrenia Bulletin 1998.24,203-218.
[120]Friston, K.J., Frith, C.D., Schizophrenia-a Disconnection Syndrome. Clinical Neuroscience 1995.3,89-97.
[121]Paulus, M.P., Hozack, N.E., Zauscher, B.E., Frank, L., Brown, G.G., McDowell, J., Braff, D.L., Parietal dysfunction is associated with increased outcome-related decision-making in schizophrenia patients. Biological Psychiatry 2002.51,995-1004.
[122]Tan, H.Y., Sust, S., Buckholtz, J.W., Mattay, V.S., Meyer-Lindenberg, A., Egan, M.F., Weinberger, D.R., Callicott, J.H., Dysfunctional prefrontal regional specialization and compensation in schizophrenia. American Journal of Psychiatry 2006.163,1969-1977.
[123]Kim, J.J., Kwon, J.S., Park, H.J., Youn, T., Kang, D.H., Kim, M.S., Lee, D.S., Lee, M.C., Functional disconnection between the prefrontal and parietal cortices during working memory processing in schizophrenia:A [O-15]H2O PET study. American Journal of Psychiatry 2003.160,919-923.
[124]Kim, J.J., Seok, J.H., Park, H.J., Lee, D.S., Lee, M.C., Kwon, J.S., Functional disconnection of the semantic networks in schizophrenia. Neuroreport 2005.16, 355-359.
[125]Spence, S.A., Liddle, P.F., Stefan, M.D., Hellewell, J.S.E., Sharma, T., Friston, K.J., Hirsch, S.R., Frith, C.D., Murray, R.M., Deakin, J.F.W., Grasby, P.M., Functional anatomy of verbal fluency in people with schizophrenia and those at genetic risk-Focal dysfunction and distributed disconnectivity reappraised. British Journal of Psychiatry 2000.176,52-60.
[126]Garrity, A.G., Pearlson, G.D., McKiernan, K., Lloyd, D., Kiehl, K.A., Calhoun, V.D., Aberrant "default mode" functional connectivity in schizophrenia. American Journal of Psychiatry 2007.164,450-457.
[127]Bluhm, R.L., Miller, J., Lanius, R.A., Osuch, E.A., Boksman, K., Neufeld, R.W.J., Theberge, J., Schaefer, B., Williamson, P., Spontaneous low-frequency fluctuations in the BOLD signal in schizophrenic patients:Anomalies in the default network. Schizophrenia Bulletin 2007.33,1004-1012.
[128]Liang, M., Zhou, Y., Jiang, T.Z., Liu, Z.N., Tian, L.X., Liu, H.H., Hao, Y.H., Widespread functional disconnectivity in schizophrenia with resting-state functional magnetic resonance imaging. Neuroreport 2006.17,209-213.
[129]Liu, Y., Liang, M., Zhou, Y., He, Y., Hao, Y.H., Song, M., Yu, C.S., Liu, H.H., Liu, Z.N., Jiang, T.Z., Disrupted small-world networks in schizophrenia. Brain 2008. 131,945-961.
[130]Zhou, Y., Liang, M., Tian, L.X., Wang, K., Hao, Y.H., Liu, H.H., Liu, Z.N., Jiang, T.Z., Functional disintegration in paranoid schizophrenia using resting-state fMRI. Schizophrenia Research 2007.97,194-205.
[131]Mesulam, M.M., From sensation to cognition. Brain 1998.121,1013-1052.
[132]Kay, S.R., Fiszbein, A., Opler, L.A., The Positive and Negative Syndrome Scale (Panss) for Schizophrenia. Schizophrenia Bulletin 1987.13,261-276.
[133]Dale, A.M., Fischl, B., Sereno, M.I., Cortical surface-based analysis-I. Segmentation and surface reconstruction. Neuroimage 1999.9,179-194.
[134]Fischl, B., Sereno, M.I., Dale, A.M., Cortical surface-based analysis-II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 1999.9, 195-207.
[135]Collins, D.L., Neelin, P., Peters, T.M., Evans, A.C., Automatic 3d Intersubject Registration of Mr Volumetric Data in Standardized Talairach Space. Journal of Computer Assisted Tomography 1994.18,192-205.
[136]Talairach, J., Tournoux, P., Co-Planar Stereotaxic Atlas of the Human Brain. New York:Thieme Medical Publishers 1988.
[137]Bollobas, B., Random graphs. London:Academic 1985.
[138]Achard, S., Bullmore, E., Efficiency and cost of economical brain functional networks. Plos Computational Biology 2007.3,174-183.
[139]Latora, V., Marchiori, M., Efficient behavior of small-world networks. Physical Review Letters 2001.8719.
[140]Watts, D.J., Strogatz, S.H., Collective dynamics of'small-world'networks. Nature 1998.393,440-442.
[141]Sporns, O., Honey, C.J., Kotter, R., Identification and Classification of Hubs in Brain Networks. Plos One 2007.2, e1049.
[142]Wasserman, S., Faust, K., Social Network Analysis:Methods and Applications. Cambridge Univ. Press 1994.
[143]Benjamini, Y, Hochberg, Y, Controlling the False Discovery Rate-a Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B-Methodological 1995.57,289-300.
[144]Benjamini, Y, Krieger, A.M., Yekutieli, D., Adaptive linear step-up procedures that control the false discovery rate. Biometrika 2006.93,491-507.
[145]Bullmore, E.T., Suckling, J., Overmeyer, S., Rabe-Hesketh, S., Taylor, E., Brammer, M.J., Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain. IEEE Transactions on Medical Imaging 1999.18,32-42.
[146]He, Y., Chen, Z.J., Evans, A.C., Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cerebral Cortex 2007.17,2407-2419.
[147]Mechelli, A., Friston, K.J., Frackowiak, R.S., Price, C.J., Structural covariance in the human cortex. Journal of Neuroscience 2005.25,8303-8310.
[148]Achard, S., Salvador, R., Whitcher, B., Suckling, J., Bullmore, E., A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. Journal of Neuroscience 2006.26,63-72.
[149]Sporns, O., Chialvo, D.R., Kaiser, M., Hilgetag, C.C., Organization, development and function of complex brain networks. Trends in Cognitive Sciences 2004.8,418-425.
[150]Fransson, P., Spontaneous low-frequency BOLD signal fluctuations:An fMRI investigation of the resting-state default mode of brain function hypothesis. Human Brain Mapping 2005.26,15-29.
[151]Greicius, M.D., Krasnow, B., Reiss, A.L., Menon, V., Functional connectivity in the resting brain:A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences of the United States of America 2003.100, 253-258.
[152]Gusnard, D.A., Raichle, M.E., Searching for a baseline:Functional imaging and the resting human brain. Nature Reviews Neuroscience 2001.2,685-694.
[153]Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., A default mode of brain function. Proc Natl Acad Sci U S A 2001.98, 676-682.
[154]Mason, M.F., Norton, M.I., Van Horn, J.D., Wegner, D.M., Grafton, S.T., Macrae, C.N., Wandering minds:The default network and stimulus-independent thought. Science 2007.315,393-395.
[155]Batchelder, W.H., Riefer, D.M., Multinomial Processing Models of Source Monitoring. Psychological Review 1990.97,548-564.
[156]Frith, C, Functional Imaging and Cognitive Abnormalities. Lancet 1995.346, 615-620.
[157]Neufeld, R.W., On the centrality and significance of stimulus-encoding deficit in schizophrenia. Schizophr Bull 2007.33,982-993.
[158]Weniger, G., Lange, C, Ruther, E., Irle, E., Differential impairments of facial affect recognition in schizophrenia subtypes and major depression. Psychiatry Research 2004.128,135-146.
[159]Weniger, G., Irle, E., Impaired facial affect recognition and emotional changes in subjects with transmodal cortical lesions. Cerebral Cortex 2002.12,258-268.
[160]Pearlson, G.D., Petty, R.G., Ross, C.A., Tien, A.Y., Schizophrenia:A disease of heteromodal association cortex? Neuropsychopharmacology 1996.14,1-17.
[161]Chemerinski, E., Nopoulos, P.C., Crespo-Facorro, B., Andreasen, N.C., Magnotta, V., Morphology of the ventral frontal cortex in schizophrenia:Relationship with social dysfunction. Biological Psychiatry 2002.52,1-8.
[162]Crespo-Facorro, B., Kim, J.J., Andreasen, N.C., O'Leary, D.S., Bockholt, H.J., Magnotta, V., Insular cortex abnormalities in schizophrenia:a structural magnetic resonance imaging study of first-episode patients. Schizophrenia Research 2000.46, 35-43.
[163]Hempel, A., Hempel, E., Schonknecht, P., Stippich, C., Schroder, J., Impairment in basal limbic function in schizophrenia during affect recognition. Psychiatry Research-Neuroimaging 2003.122,115-124.
[164]Sigmundsson, T., Suckling, J., Maier, M., Williams, S.C.R., Bullmore, E.T., Greenwood, K.E., Fukuda, R., Ron, M.A., Toone, B.K., Structural abnormalities in frontal, temporal, and limbic regions and interconnecting white matter tracts in schizophrenic patients with prominent negative symptoms. American Journal of Psychiatry 2001.158,234-243.
[165]Streit, M., Ioannides, A., Sinnemann, T., Wolwer, W., Dammers, J., Zilles, K., Gaebel, W., Disturbed facial affect recognition in patients with schizophrenia associated with hypoactivity in distributed brain regions:A magnetoencephalographic study. American Journal of Psychiatry 2001.158,1429-1436.
[166]Olabarriaga, S.D., Smeulders, A.W., Interaction in the segmentation of medical images:a survey. Medical Image Analysis 2001.5,127-142.
[167]Pham, D.L., Xu, C.Y., Prince, J.L., Current methods in medical image segmentation. Annual Review of Biomedical Engineering 2000.2,315-337.
[168]Sahoo, P.K., Soltani, S., Wong, A.K.C., Chen, Y.C., A Survey of Thresholding Techniques. Computer Vision Graphics and Image Processing 1988.41,233-260.
[169]Prewitt, J.M.S., Object enhancement and extraction. Picture processing and Psychopictorics 1970. in B.S. Lipkin and A. Rosenfeld (Eds.), Academic Press.
[170]Canny, J., A Computational Approach to Edge-Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 1986.8,679-698.
[171]Schnack, H.G., Pol, H.E.H, Baare, W.F.C., Viergever, M.A., Kahn, R.S., Automatic segmentation of the ventricular system from MR images of the human brain. Neuroimage 2001.14,95-104.
[172]Tang, H., Wu, E.X., Ma, Q.Y, Gallagher, D., Perera, G.M., Zhuang, T., MRI brain image segmentation by multi-resolution edge detection and region selection. Computerized Medical Imaging and Graphics 2000.24,349-357.
[173]Zhu, S.C., Yuille, A., Region competition:Unifying snakes, region growing, and Bayes/MDL for multiband image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 1996.18,884-900.
[174]Clarke, L.P., Velthuizen, R.P., Camacho, M.A., Heine, J.J., Vaidyanathan, M., Hall, L.O., Thatcher, R.W., Silbiger, M.L., Mri Segmentation-Methods and Applications. Magnetic Resonance Imaging 1995.13,343-368.
[175]Withey, D.J., Koles, Z.J., Medical image segmentation:Methods and software. 2007 Joint Meeting of the 6th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging 2007.143-146.
[176]Pina, R.K., Puetter, R.C., Bayesian Image-Reconstruction-the Pixon and Optimal Image Modeling. Publications of the Astronomical Society of the Pacific 1993.105,630-637.
[177]Descombes, X., Kruggel, F., A Markov pixon information approach for low-level image description. IEEE Transactions on Pattern Analysis and Machine Intelligence 1999.21,482-494.
[178]Lin, L., Zhu, L.T., Yang, F.G., Jiang, T.Z., A novel pixon-representation for image segmentation based on Markov random field. Image and Vision Computing 2008.26,1507-1514.
[179]Yang, F.G., Jiang, T.Z., Pixon-based image segmentation with Markov random fields. IEEE Transactions on Image Processing 2003.12,1552-1559.
[180]Fukunaga, K., Hostetler, L.D., Estimation of Gradient of a Density-Function, with Applications in Pattern-Recognition. IEEE Transactions on Information Theory 1975. It21,32-40.
[181]Jimenez-Alaniz, J.R., Medina-Banuelos, V., Yanez-Suarez, O., Data-driven brain MRI segmentation supported on edge confidence and A priori tissue information. IEEE Transactions on Medical Imaging 2006.25,74-83.
[182]Cheng, Y.Z., Mean Shift, Mode Seeking, and Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 1995.17,790-799.
[183]Comaniciu, D., Meer, P., Mean shift:A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 2002.24, 603-619.
[184]Comaniciu, D., Ramesh, V, Meer, P., The variable bandwidth mean shift and data-driven scale selection. Eighth IEEE International Conference on Computer Vision, Vol I, Proceedings 2001.438-445.
[185]Wells, W.M., Grimson, W.E.L., Kikinis, R., Jolesz, F.A., Adaptive segmentation of MRI data. IEEE Transactions on Medical Imaging 1996.15,429-442.
[186]Besag, J., On the Statistical-Analysis of Dirty Pictures. Journal of the Royal Statistical Society Series B-Methodological 1986.48,259-302.
[187]Andrey, P., Tarroux, P., Unsupervised segmentation of Markov random field modeled textured images using selectionist relaxation. Ieee Transactions on Pattern Analysis and Machine Intelligence 1998.20,252-262.
[188]Held, K., Kops, E.R., Krause, B.J., Wells, W.M., Kikinis, R., Muller-Gartner, H.W., Markov random field segmentation of brain MR images. IEEE Transactions on Medical Imaging 1997.16,878-886.
[189]Kato, Z., Zerubia, J., Berthod, M., Unsupervised parallel image classification using Markovian models. Pattern Recognition 1999.32,591-604.
[190]Kwan, R.K.S., Evans, A.C., Pike, G.B., MRI simulation-based evaluation of image-processing and classification methods. IEEE Transactions on Medical Imaging 1999.18,1085-1097.
[191]Cocosco, C.A., Kollokian, V., Kwan, R.K.S., Evans, A.C., Brainweb:online interface to a 3D MRI simulated brain database. Neuroimage 1997.5, S425.
[192]Hasanzadeh, M., Kasaei, S., Fuzzy Image Segmentation Using Membership Connectedness. Eurasip Journal on Advances in Signal Processing 2008.
[193]Zhou, Y.X., Bai, J., Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI. IEEE Transactions on Biomedical Engineering 2007.54,122-129.
[194]Ibrahim, M., John, N., Kabuka, M., Younis, A., Hidden Markov models-based 3D MRI brain segmentation. Image and Vision Computing 2006.24,1065-1079.
[195]Rivera, M., Ocegueda, O., Marroquin, J.L., Entropy-controlled quadratic Markov measure field models for efficient image segmentation. IEEE Transactions on Image Processing 2007.16,3047-3057.
[196]Solomon, J., Butman, J.A., Sood, A., Segmentation of brain tumors in 4D MR images using the hidden Markov model. Computer Methods and Programs in Biomedicine 2006.84,76-85.
[197]Shattuck, D.W., Sandor-Leahy, S.R., Schaper, K.A., Rottenberg, D.A., Leahy, R.M., Magnetic resonance image tissue classification using a partial volume model. Neuroimage 2001.13,856-876.
[198]Siyal, M.Y., Yu, L., An intelligent modified fuzzy c-means based algorithm for bias estimation and segmentation of brain MRI. Pattern Recognition Letters 2005.26, 2052-2062.