Academic literature on the topic 'Tensor-based morphometry'
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Journal articles on the topic "Tensor-based morphometry"
Ashburner, John, Catriona Good, and Karl J. Friston. "Tensor based morphometry." NeuroImage 11, no. 5 (May 2000): S465. http://dx.doi.org/10.1016/s1053-8119(00)91396-x.
Full textWang, Y., X. Gu, T. F. Chan, A. W. Toga, and P. M. Thompson. "Multivariate Statistics of Tensor-Based Cortical Surface Morphometry." NeuroImage 47 (July 2009): S100. http://dx.doi.org/10.1016/s1053-8119(09)70850-x.
Full textMuñoz-Ruiz, Miguel Ángel, Päivi Hartikainen, Juha Koikkalainen, Robin Wolz, Valtteri Julkunen, Eini Niskanen, Sanna-Kaisa Herukka, et al. "Structural MRI in Frontotemporal Dementia: Comparisons between Hippocampal Volumetry, Tensor-Based Morphometry and Voxel-Based Morphometry." PLoS ONE 7, no. 12 (December 20, 2012): e52531. http://dx.doi.org/10.1371/journal.pone.0052531.
Full textKhan, Ali R., Lei Wang, and Mirza Faisal Beg. "Unified voxel- and tensor-based morphometry (UVTBM) using registration confidence." Neurobiology of Aging 36 (January 2015): S60—S68. http://dx.doi.org/10.1016/j.neurobiolaging.2014.04.036.
Full textChung, M. K., K. M. Dalton, and R. J. Davidson. "Tensor-Based Cortical Surface Morphometry via Weighted Spherical Harmonic Representation." IEEE Transactions on Medical Imaging 27, no. 8 (August 2008): 1143–51. http://dx.doi.org/10.1109/tmi.2008.918338.
Full textYanovsky, Igor, Alex D. Leow, Suh Lee, Stanley J. Osher, and Paul M. Thompson. "Comparing registration methods for mapping brain change using tensor-based morphometry." Medical Image Analysis 13, no. 5 (October 2009): 679–700. http://dx.doi.org/10.1016/j.media.2009.06.002.
Full textKoikkalainen, Juha, Jyrki Lötjönen, Lennart Thurfjell, Daniel Rueckert, Gunhild Waldemar, and Hilkka Soininen. "Multi-template tensor-based morphometry: Application to analysis of Alzheimer's disease." NeuroImage 56, no. 3 (June 2011): 1134–44. http://dx.doi.org/10.1016/j.neuroimage.2011.03.029.
Full textLandin-Romero, Ramón, Erick J. Canales-Rodríguez, Fiona Kumfor, Ana Moreno-Alcázar, Mercè Madre, Teresa Maristany, Edith Pomarol-Clotet, and Benedikt L. Amann. "Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder." Australian & New Zealand Journal of Psychiatry 51, no. 1 (July 11, 2016): 42–54. http://dx.doi.org/10.1177/0004867416631827.
Full textTao, Guozhi, Sushmita Datta, Renjie He, Flavia Nelson, Jerry S. Wolinsky, and Ponnada A. Narayana. "Deep gray matter atrophy in multiple sclerosis: A tensor based morphometry." Journal of the Neurological Sciences 282, no. 1-2 (July 2009): 39–46. http://dx.doi.org/10.1016/j.jns.2008.12.035.
Full textWhitwell, Jennifer L., Joseph R. Duffy, Mary M. Machulda, Heather M. Clark, Edythe A. Strand, Matthew L. Senjem, Jeffrey L. Gunter, et al. "Tracking the development of agrammatic aphasia: A tensor-based morphometry study." Cortex 90 (May 2017): 138–48. http://dx.doi.org/10.1016/j.cortex.2016.09.017.
Full textDissertations / Theses on the topic "Tensor-based morphometry"
Brun, Caroline Chantal Dominique. "A new Riemannian fluid registration algorithm with Lagrangian dissipation and its application to tensor-based morphometry." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1872911431&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
Full textHua, Xue. "The application of tensor based morphometry in mapping human brain anatomical changes during normal and pathological conditions." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1779690341&sid=8&Fmt=2&clientId=1564&RQT=309&VName=PQD.
Full textWhitford, Thomas James. "A longitudinal study of brain structure in the early stages of schizophrenia." University of Sydney, 2007. http://hdl.handle.net/2123/1895.
Full textSchizophrenia is a severe mental illness that affects approximately 1% of the population worldwide, and which typically has a devastating effect on the lives of its sufferers. The characteristic symptoms of the disease include hallucinations, delusions, disorganized thought and reduced emotional expression. While many of the early theories of schizophrenia focused on its psychosocial foundations, more recent theories have focused on the neurobiological underpinnings of the disease. This thesis has four primary aims: 1) to use magnetic resonance imaging (MRI) to identify the structural brain abnormalities present in patients suffering from their first episode of schizophrenia (FES), 2) to elucidate whether these abnormalities were static or progressive over the first 2-3 years of patients’ illness, 3) to identify the relationship between these neuroanatomical abnormalities and patients’ clinical profile, and 4) to identify the normative relationship between longitudinal changes in neuroanatomy and electrophysiology in healthy participants, and to compare this to the relationship observed between these two indices in patients with FES. The aim of Chapter 2 was to use MRI to identify the neuroanatomical changes that occur over adolescence in healthy participants, and to identify the normative relationship between the neuroanatomical changes and electrophysiological changes associated with healthy periadolescent brain maturation. MRI and electroencephalographic (EEG) scans were acquired from 138 healthy participants between the ages of 10 and 30 years. The MRI scans were segmented into grey matter (GM) and white matter (WM) images, before being parcellated into the frontal, temporal, parietal and occipital lobes. Absolute EEG power was calculated for the slow-wave, alpha and beta frequency bands, for the corresponding cortical regions. The age-related changes in regional tissue volumes and regional EEG power were inferred with a regression model. The results indicated that the healthy participants experienced accelerated GM loss, EEG power loss and WM gain in the frontal and parietal lobes between the ages of 10 and 20 years, which decelerated between the ages of 20 and 30 years. A linear relationship was also observed between the maturational changes in regional GM volumes and EEG power in the frontal and parietal lobes. These results indicate that the periadolescent period is a time of great structural and electrophysiological change in the healthy human brain. The aim of Chapter 3 was to identify the GM abnormalities present in patients with FES, both at the time of their first presentation to mental health services (baseline), and over the first 2-3 years of their illness (follow-up). MRI scans were acquired from 41 patients with FES at baseline, and 47 matched healthy control subjects. Of these participants, 25 FES patients and 26 controls returned 2-3 years later for a follow-up scan. The analysis technique of voxel-based morphometry (VBM) was used in conjunction with the Statistical Parametric Mapping (SPM) software package in order to identify the regions of GM difference between the groups at baseline. The related analysis technique of tensor-based morphometry (TBM) was used to identify subjects’ longitudinal GM change over the follow-up interval. Relative to the healthy controls, the FES patients were observed to exhibit widespread GM reductions in the frontal, parietal and temporal cortices and cerebellum at baseline, as well as more circumscribed regions of GM increase, particularly in the occipital lobe. Furthermore, the FES patients lost considerably more GM over the follow-up interval than the controls, particularly in the parietal and temporal cortices. These results indicate that patients with FES exhibit significant structural brain abnormalities very early in the course of their illness, and that these abnormalities progress over the first few years of their illness. Chapter 4 employed the same methodology to investigate the white matter abnormalities exhibited by the FES subjects relative to the controls, both at baseline and over the follow-up interval. Compared to controls, the FES patients exhibited volumetric WM deficits in the frontal and temporal lobes at baseline, as well as volumetric increases at the fronto-parietal junction bilaterally. Furthermore, the FES patients lost considerably more WM over the follow-up interval than did the controls in the middle and inferior temporal cortex bilaterally. While there is substantial evidence indicating that abnormalities in the maturational processes of myelination play a significant role in the development of WM abnormalities in FES, the observed longitudinal reductions in WM were consistent with the death of a select population of temporal lobe neurons over the follow-up interval. The aim of Chapter 5 was to investigate the clinical correlates of the GM abnormalities exhibited by the FES patients at baseline. The volumes of four distinct cerebral regions where 31 patients with FES exhibited reduced GM volumes relative to 30 matched controls were calculated and correlated with patients’ scores on three primary symptom dimensions: Disorganization, Reality Distortion and Psychomotor Poverty. The results indicated that the greater the degree of atrophy exhibited by the FES patients in three of these four ‘regions-of-reduction’, the less severe their degree of Reality Distortion. These results suggest that an excessive amount of GM atrophy may in fact preclude the formation of hallucinations or highly systematized delusions in patients with FES. The aim of Chapter 6 was to identify the relationship between the longitudinal changes in brain structure and brain electrophysiology exhibited by 19 FES patients over the first 2-3 years of their illness, and to compare it to the normative relationship between the two indices reported in Chapter 2. The methodology employed for the parcellation of the MRI and EEG data was identical to Chapter 2. The results indicated that, in contrast to the healthy controls, the longitudinal reduction in GM volume exhibited by the FES patients was not associated with a corresponding reduction in EEG power in any brain lobe. In contrast, EEG power was observed to be maintained or even to increase over the follow-up interval in these patients. These results were consistent with the FES patients experiencing an abnormal elevation of neural synchrony. Such an abnormality in neural synchrony could potentially form the basis of the dysfunctional neural connectivity that has been widely proposed to underlie the functional deficits present in patients with schizophrenia. The primary aim of Chapter 7 was to assimilate the findings from the preceding empirical chapters with the theoretical framework provided in the literature, into an integrated and testable model of schizophrenia. The model emphasized dysfunctions in brain maturation, specifically in the normative processes of synaptic ‘pruning’ and axonal myelination, as playing a key role in the development of disintegrated neural activity and the subsequent onset of schizophrenic symptoms. The model concluded with the novel proposal that disintegrated neural activity arises from abnormal elevations in the synchrony of synaptic activity in patients with first-episode schizophrenia.
Beckwith, Travis J. "A Magnetic Resonance Imaging Study of the Developmental Consequences of Childhood Lead Exposure in Adulthood." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439309120.
Full textDelmaire, Christine. "Exploration in vivo grâce à l'IRM des atteintes fonctionnelles, morphologiques et microstructurelles dans la dystonie." Paris 6, 2007. http://www.theses.fr/2007PA066595.
Full textDystonia is a movement disorder whose pathophysiology is not fully understood. To date, conventional MR imaging was unsuccessful in showing structural abnormality in primary dystonia. New recent imaging techniques, such as voxel based morphometry (VBM) and diffusion tensor imaging (DTI), can be utilized to explore more precisely the pathophysiology of dystonia. In this work, we used several MRI methods to investigate the pathophysiology of dystonia. We used fMRI to determine whether the selectivity of neuronal representation of basal ganglia neurons was altered in the putamen of patients with focal hand dystonia before and after rehabilitation. Using voxel-based morphometry and DTI, we tested the hypothesis that structural or microstructural changes occur in the sensorimotor basal ganglia - cortical circuit in primary focal hand dystonia. Lastly, we combined structural imaging and fiber tracking to determine the functionnal territory of the basal ganglia that is damaged in post stroke dystonia. Overall, our results show that cortico striatal thalamo cerebellar sensorimotor circuit is likely to play a fundamental role in the pathophysiology of the dystonia
Yip, S. W. "The bipolar phenotype : behavioural and neurobiological characteristics." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:b7091bbc-27c7-4377-a475-601bb6010440.
Full textBorlase, Nadia Miree. "The thalamus in Parkinson's disease: a multimodal investigation of thalamic involvement in cognitive impairment." Thesis, University of Canterbury. Psychology, 2013. http://hdl.handle.net/10092/8689.
Full textCarmo, Samuel Sullivan. "Características do envolvimento do Sistema Nervoso Central na Polirradiculoneuropatia Inflamatória Desmielinizante Crônica: um estudo mediante técnicas quantitativas de Imagem por Ressonância Magnética." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/17/17140/tde-16092014-170302/.
Full textChronic Inflammatory Demyelinating Polyneuropathy (CIDP) is a severe disease fundamentally characterized by dysfunction of the Peripheral Nervous System and affects greatly the quality of life of patients. The Central Nervous System (CNS) involvement in CIDP has not been described using recent quantitative neuroimaging techniques. We evaluated 11 patients with CIDP, all treated and without clinical signs of central alterations and 11 controls matched for gender and age group of 19 to 69 years. Magnetic Resonance Imaging were performed on a 3T scanner using different imaging techniques; structural 3D T1-weighted, fluid-attenuated inversion recovery, relaxometry with 5 echoes pulse sequence for T2 maps, magnetization transfer weighted and diffusion tensor imaging. The images were processed on different tools and were obtained results for the studies of diffusivity, volumetry, morphometry, tractometry, brain connectivity, and radiological findings of patients. Different statistical group analyses were performed in the quantitative results: 1) Parametric test for volumetry, tractometry and brain connectivity; 2) Parametric mapping for voxel morphometry; 3) Tract-based spatial statistics (TBSS) for diffusion coefficients. Changes were detected in all comparisons. In the patients, our main findings are: generalized loss brain volume more pronounced in periventricular regions associated with prominent ventricles, increased simultaneously perpendiculars and parallel diffusivity in the major tracts of the TBSS analyze, white matter density loss in the periventricular area, some bilateral trigeminal thickening, and general reduction of the brain connectivity. The CIDP affects the global brain and represents a demyelination in the CNS.
"Combining Thickness Information with Surface Tensor-based Morphometry for the 3D Statistical Analysis of the Corpus Callosum." Master's thesis, 2013. http://hdl.handle.net/2286/R.I.20930.
Full textDissertation/Thesis
M.S. Computer Science 2013
Moayedi, Massieh. "Structural Brain Abnormalities in Temporomandibular Disorders." Thesis, 2012. http://hdl.handle.net/1807/34816.
Full textBooks on the topic "Tensor-based morphometry"
Boedhoe, Premika S. W., and Odile A. van den Heuvel. The Structure of the OCD Brain. Edited by Christopher Pittenger. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228163.003.0023.
Full textBook chapters on the topic "Tensor-based morphometry"
Ingalhalikar, Madhura, Parmeshwar Khurd, and Ragini Verma. "Kernel-Based Morphometry of Diffusion Tensor Images." In Mathematics and Visualization, 229–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54301-2_10.
Full textLeporé, Natasha, Caroline Brun, Xavier Pennec, Yi-Yu Chou, Oscar L. Lopez, Howard J. Aizenstein, James T. Becker, Arthur W. Toga, and Paul M. Thompson. "Mean Template for Tensor-Based Morphometry Using Deformation Tensors." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007, 826–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75759-7_100.
Full textShi, Jie, Paul M. Thompson, and Yalin Wang. "Human Brain Mapping with Conformal Geometry and Multivariate Tensor-Based Morphometry." In Multimodal Brain Image Analysis, 126–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24446-9_16.
Full textWang, Yalin, Tony F. Chan, Arthur W. Toga, and Paul M. Thompson. "Multivariate Tensor-Based Brain Anatomical Surface Morphometry via Holomorphic One-Forms." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, 337–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04268-3_42.
Full textZhang, Hui, Paul A. Yushkevich, Daniel Rueckert, and James C. Gee. "Tensor-Based Morphometry of Fibrous Structures with Application to Human Brain White Matter." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, 466–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04271-3_57.
Full textBossa, Matías Nicolás, Ernesto Zacur, and Salvador Olmos. "Tensor-Based Morphometry with Mappings Parameterized by Stationary Velocity Fields in Alzheimer’s Disease Neuroimaging Initiative." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, 240–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04271-3_30.
Full textLepore, Natasha, Caroline A. Brun, Ming-Chang Chiang, Yi-Yu Chou, Rebecca A. Dutton, Kiralee M. Hayashi, Oscar L. Lopez, et al. "Multivariate Statistics of the Jacobian Matrices in Tensor Based Morphometry and Their Application to HIV/AIDS." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006, 191–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11866565_24.
Full textBrun, Caroline, Natasha Leporé, Xavier Pennec, Yi-Yu Chou, Agatha D. Lee, Marina Barysheva, Grieg de Zubicaray, et al. "A Tensor-Based Morphometry Study of Genetic Influences on Brain Structure Using a New Fluid Registration Method." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008, 914–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-85990-1_110.
Full textAshburner, J., and G. R. Ridgway. "Tensor-Based Morphometry." In Brain Mapping, 383–94. Elsevier, 2015. http://dx.doi.org/10.1016/b978-0-12-397025-1.00309-2.
Full text"Tensor-Based Morphometry." In Computational Neuroanatomy, 49–68. WORLD SCIENTIFIC, 2012. http://dx.doi.org/10.1142/9789814335447_0003.
Full textConference papers on the topic "Tensor-based morphometry"
Kim, Seung-Goo, Moo K. Chung, Jamie L. Hanson, Brian B. Avants, James C. Gee, Richard J. Davidson, and Seth D. Pollak. "Structural connectivity via the tensor-based morphometry." In 2011 8th IEEE International Symposium on Biomedical Imaging (ISBI 2011). IEEE, 2011. http://dx.doi.org/10.1109/isbi.2011.5872528.
Full textPaniagua, Beatriz, Abeer Alhadidi, Lucia Cevidanes, Martin Styner, and Ipek Oguz. "Mandibular asymmetry characterization using generalized tensor-based morphometry." In 2011 8th IEEE International Symposium on Biomedical Imaging (ISBI 2011). IEEE, 2011. http://dx.doi.org/10.1109/isbi.2011.5872611.
Full textVillalon, Julio, Anand A. Joshi, Natasha Lepore, Caroline Brun, Arthur W. Toga, and Paul M. Thompson. "Comparison of volumetric registration algorithms for tensor-based morphometry." In 2011 8th IEEE International Symposium on Biomedical Imaging (ISBI 2011). IEEE, 2011. http://dx.doi.org/10.1109/isbi.2011.5872694.
Full textRajagopalan, Vidya, Armin Schwartzman, Xue Hua, Alex Leow, Paul Thompson, and Natasha Lepore. "Multivariate analysis of eigenvalues and eigenvectors in tensor based morphometry." In Tenth International Symposium on Medical Information Processing and Analysis, edited by Eduardo Romero and Natasha Lepore. SPIE, 2015. http://dx.doi.org/10.1117/12.2073737.
Full textYalin Wang, Tony F. Chan, Arthur W. Toga, and Paul M. Thompson. "Shape analysis with multivariate tensor-based morphometry and holomorphic differentials." In 2009 IEEE 12th International Conference on Computer Vision (ICCV). IEEE, 2009. http://dx.doi.org/10.1109/iccv.2009.5459422.
Full textMichalkiewicz, Mateusz, Akshay Pai, Kelvin K. Leung, Stefan Sommer, Sune Darkner, Lauge Sørensen, Jon Sporring, and Mads Nielsen. "Combining the boundary shift integral and tensor-based morphometry for brain atrophy estimation." In SPIE Medical Imaging, edited by Martin A. Styner and Elsa D. Angelini. SPIE, 2016. http://dx.doi.org/10.1117/12.2217089.
Full textZhang, Jie, Cynthia Stonnington, Qingyang Li, Jie Shi, Robert J. Bauer, Boris A. Gutman, Kewei Chen, et al. "Applying sparse coding to surface multivariate tensor-based morphometry to predict future cognitive decline." In 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016). IEEE, 2016. http://dx.doi.org/10.1109/isbi.2016.7493350.
Full textWang, Yalin, Jie Zhang, Tony F. Chan, Arthur W. Toga, and Paul M. Thompson. "Multivariate tensor-based morphometry on surfaces: Application to mapping ventricular changes in HIV/AIDS." In 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI). IEEE, 2009. http://dx.doi.org/10.1109/isbi.2009.5193000.
Full textKim, Seung-Goo, Brian B. Avants, Hyekyoung Lee, James C. Gee, Moo K. Chung, Richard J. Davidson, Jamie L. Hanson, and Seth D. Pollak. "Agreement between the white matter connectivity based on the tensor-based morphometry and the volumetric white matter parcellations based on diffusion tensor imaging." In 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012). IEEE, 2012. http://dx.doi.org/10.1109/isbi.2012.6235479.
Full textLi, Wenjing, Huiguang He, Jingjing Lu, Bin Lv, Meng Li, and Zhengyu Jin. "Detection of whole-brain abnormalities in temporal lobe epilepsy using tensor-based morphometry with DARTEL." In Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, edited by Jianguo Liu, Kunio Doi, Aaron Fenster, and S. C. Chan. SPIE, 2009. http://dx.doi.org/10.1117/12.833128.
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