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Статті в журналах з теми "MRI, Diffusion, MEG"
Lambregts, Doenja M. J., Milou H. Martens, Raymond C. W. Quah, Katerina Nikiforaki, Luc A. Heijnen, Cornelis H. C. Dejong, Geerard L. Beets, Kostas Marias, Nickolas Papanikolaou, and Regina G. H. Beets-Tan. "Whole-liver diffusion-weighted MRI histogram analysis." European Journal of Gastroenterology & Hepatology 27, no. 4 (April 2015): 399–404. http://dx.doi.org/10.1097/meg.0000000000000316.
Повний текст джерелаDeslauriers-Gauthier, Samuel, Isa Costantini, and Rachid Deriche. "Non–invasive inference of information flow using diffusion MRI, functional MRI, and MEG." Journal of Neural Engineering 17, no. 4 (July 10, 2020): 045003. http://dx.doi.org/10.1088/1741-2552/ab95ec.
Повний текст джерелаTrojsi, Francesca, Pierpaolo Sorrentino, Giuseppe Sorrentino, and Gioacchino Tedeschi. "Neurodegeneration of brain networks in the amyotrophic lateral sclerosis–frontotemporal lobar degeneration (ALS–FTLD) continuum: evidence from MRI and MEG studies." CNS Spectrums 23, no. 6 (October 27, 2017): 378–87. http://dx.doi.org/10.1017/s109285291700075x.
Повний текст джерелаLee, Yun Jeong. "Advanced neuroimaging techniques for evaluating pediatric epilepsy." Clinical and Experimental Pediatrics 63, no. 3 (March 15, 2020): 88–95. http://dx.doi.org/10.3345/kjp.2019.00871.
Повний текст джерелаAllen, Christopher, Lukas Rier, Lauren Gascoyne, Robert Dineen, Roshan DasNair, Matthew Brookes, and Nikos Evangelou. "164 The role of MEG in assessment and diagnosis in mTBI." Journal of Neurology, Neurosurgery & Psychiatry 93, no. 9 (August 12, 2022): e2.122. http://dx.doi.org/10.1136/jnnp-2022-abn2.208.
Повний текст джерелаRichards, Todd L. "Functional Magnetic Resonance Imaging and Spectroscopic Imaging of the Brain: Application of fmri and fmrs to Reading Disabilities and Education." Learning Disability Quarterly 24, no. 3 (August 2001): 189–203. http://dx.doi.org/10.2307/1511243.
Повний текст джерелаSidiropoulos, Christos, Susan M. Bowyer, Andrew Zillgitt, Peter A. LeWitt, Hassan Bagher-Ebadian, Esmaeil Davoodi-Bojd, Jason M. Schwalb, Richard Rammo, Ellen Air, and Hamid Soltanian-Zadeh. "Multimodal Imaging in a Patient with Hemidystonia Responsive to GPi Deep Brain Stimulation." Case Reports in Neurological Medicine 2017 (2017): 1–4. http://dx.doi.org/10.1155/2017/9653520.
Повний текст джерелаKamada, Kyousuke, Kiyohiro Houkin, Fumiya Takeuchi, Nobuaki Ishii, Jun Ikeda, Yutaka Sawamura, Shinya Kuriki, Kawaguchi, and Yoshinobu Iwasaki. "Visualization of the eloquent motor system by integration of MEG, functional, and anisotropic diffusion-weighted MRI in functional neuronavigation." Surgical Neurology 59, no. 5 (May 2003): 352–60. http://dx.doi.org/10.1016/s0090-3019(03)00018-1.
Повний текст джерелаRenga, Vijay. "Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis." Neurology Research International 2022 (February 7, 2022): 1–20. http://dx.doi.org/10.1155/2022/1838682.
Повний текст джерелаAqil, Marco, Selen Atasoy, Morten L. Kringelbach, and Rikkert Hindriks. "Graph neural fields: A framework for spatiotemporal dynamical models on the human connectome." PLOS Computational Biology 17, no. 1 (January 28, 2021): e1008310. http://dx.doi.org/10.1371/journal.pcbi.1008310.
Повний текст джерелаДисертації з теми "MRI, Diffusion, MEG"
Philippe, Anne-Charlotte. "Régularisation du problème inverse MEG par IRM de diffusion." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00939159.
Повний текст джерелаPASQUINI, JACOPO. "Multimodal Magnetic Resonance Imaging for the identification of early Multiple System Atrophy biomarkers." Doctoral thesis, Università degli Studi di Milano, 2022. http://hdl.handle.net/2434/890787.
Повний текст джерелаLAPUCCI, CATERINA. "ADVANCED SUSCEPTIBILITY AND DIFFUSION WEIGHTED IMAGING IN THE DIAGNOSIS OF MULTIPLE SCLEROSIS: FROM RESEARCH TO CLINICAL APPLICATIONS." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1088218.
Повний текст джерелаPIAGGIO, NICCOLO'. "MICROSTRUCTURAL WHITE MATTER PROPERTIES IN MULTIPLE SCLEROSIS: ANATOMICAL SPATIAL MAPPING VIA NODDI MODELLING TO BETTER UNDERSTAND THE MECHANISM OF INJURY." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1046511.
Повний текст джерелаMarizzoni, M. "DEVELOPMENT OF IMAGING MARKERS TO TRACK ALZHEIMER¿S DISEASE PROGRESSION IN HUMANS AND MOUSE MODELS." Doctoral thesis, Università degli Studi di Milano, 2013. http://hdl.handle.net/2434/217458.
Повний текст джерелаAlzheimer’s disease (AD) is the most common form of dementia in elderly population, affecting more than 35 million people worldwide. To date, the only approved therapies for AD focus on symptomatic relief. The development of new therapeutic agents is time consuming and costly. Drug discovery process is arduous because clinical trials are currently involving too wide sample of patients and long follow-up. Moreover, the predicting value of experimental models used nowadays is limited due to the lack of homologous markers in humans and animals. This work is a branch of Pharmacog, an industry-academic European project aimed at identifying reliable biomarkers that are sensitive to disease progression in patients with Mild Cognitive Impairment (MCI) and in AD animal models in order to bridge the gap between preclinical and clinical outcomes. Human neuroimaging markers are among the most promising candidates to track disease progression. In addition, advanced magnetic resonance imaging (MRI) allow the identification of homologous biomarkers in humans and mice. Prior to investigate neuroimaging biomarkers on MCI patients, we have to test that there is no significant effect of within and across MRI sites variability on brain AD-related longitudinal changes. The first aim of this work is the study of the morphometric and diffusion changes in three different AD mouse model (TASTPM, TauPS2APP and PDAPP from 3 to 22 months of age) through MRI. We found significant volume reduction starting at 9 months in the caudate-putamen and frontal cortex of TASTPM and TauPS2APP (p< 0.001) compared to non transgenic mice. The decrease in the enthorinal cortex thickness was significantly lower in all the strains (p< 0.001). We also found age-related diffusion abnormalities in different white matter regions of TASTPM. The earlier changes were found in the corpus callosum and anterior commissure of 13 months old mice (p< 0.001). In TASTPM, deficits detected with MRI are related to heavy amyloid pathology, marked gliosis and astrocitosys. The second aim of this study is the evaluation and comparison of test-retest reproducibility of brain volumes and thicknesses by two existing Freesurfer pipelines (longitudinal and cross-sectional). Moreover, we assessed the reliability of a diffusion pipeline developed in our lab. Eight different 3T MRI sites in Europe enrolled a group of 5 healthy elderly subjects scanned twice at least a week apart. We found that the within and across sites variability of volumes was less than 3% for larger brain structures (such as thalamus) and less than 6% for smaller regions (i.e., hippocampus). The thickness variability was less than 6% and diffusion indices variations were mostly within the range 2-3%. In conclusion, the present data identify imaging biomarkers of disease progression in mice similar to that seen in humans and pave the way of a murine “imaging signature” usefulness in clinical trials. Human data show significantly higher reproducibility of brain morphometry using the longitudinal pipeline than using the cross-sectional one (p< 0.01). Finally, we demonstrated that the reliability of the analysis of brain diffusion we implemented in our lab is comparable to data reported in the literature.
Silvia, Obertino. "Studying brain connectivity: a new multimodal approach for structure and function integration ." Doctoral thesis, 2019. http://hdl.handle.net/11562/995190.
Повний текст джерелаThe brain is a complex system of which anatomical and functional organization is both segregated and integrated. A longstanding question for the neuroscience community has been to elucidate the mutual influences between structure and function. To that aim, first, structural and functional connectivity need to be explored individually. Structural connectivity can be measured by the Diffusion Magnetic Resonance signal followed by successive computational steps up to virtual tractography. Functional connectivity can be established by correlation between the brain activity time courses measured by different modalities, such as functional Magnetic Resonance Imaging or Electro/Magneto Encephalography. Recently, the Graph Signal Processing (GSP) framework has provided a new way to jointly analyse structure and function. In particular, this framework extends and generalizes many classical signal-processing operations to graphs (e.g., spectral analysis, filtering, and so on). The graph here is built by the structural connectome; i.e., the anatomical backbone of the brain where nodes represent brain regions and edge weights strength of structural connectivity. The functional signals are considered as time-dependent graph signals; i.e., measures associated to the nodes of the graph. The concept of the Graph Fourier Transform then allows decomposing regional functional signals into, on one side, a portion that strongly aligned with the underlying structural network (“aligned"), and, on the other side, a portion that is not well aligned with structure (“liberal"). The proportion of aligned-vs-liberal energy in functional signals has been associated with cognitive flexibility. However, the interpretation of these multimodal relationships is still limited and unexplored for higher temporal resolution functional signals such as M/EEG. Moreover, the construction of the structural connectome itself using tractography is still a challenging topic, for which, in the last decade, many new advanced models were proposed, but their impact on the connectome remains unclear. In the first part of this thesis, I disentangled the variability of tractograms derived from different tractography methods, comparing them with a test-retest paradigm, which allows to define specificity and sensitivity of each model. I want to find the best trade-off between specificity and sensitivity to define the best model that can be deployed for analysis of functional signals. Moreover, I addressed the issue of weighing the graph comparing few estimates, highlighting the sufficiency of binary connectivity, and the power of the latest-generation microstructural properties in clinical applications. In the second part, I developed a GSP method that allows applying the aligned and liberal filters to M/EEG signals. The model extends the structural constraints to consider indirect connections, which recently demonstrated to be powerful in the structure/function link. I then show that it is possible to identify dynamic changes in aligned-vs-liberal energy, highlighting fluctuations present motor task and resting state. This model opens the perspective of novel biomarkers. Indeed, M/EEG are often used in clinical applications; e.g., multimodal integration in data from Parkinson’s disease or stroke could combine changes of both structural and functional connectivity.
CAPORALE, ALESSANDRA. "A novel mechanism of contrast in MRI: pseudo super-diffusion of water molecules unveils microstructural details in biological tissues." Doctoral thesis, 2017. http://hdl.handle.net/11573/942463.
Повний текст джерелаHUANG, XIU-WEN, and 黃綉紋. "Research on Electronic word-of-mouth diffusion path of social marketing: A Case Study of I-MEI Milk Tea." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/9jr729.
Повний текст джерела東吳大學
巨量資料管理學院碩士學位學程
107
The use of social media has become an irreversible phenomenon in the world. The new social media platforms are emerging one after another. The number of social media users has also grown year by year. Due to the rise of social media and the diversification of information dissemination, consumers can obtain the information through multiple channels. This phenomenon has greatly changed the behavior of consumers and their decision-making process of purchasing, and prompted companies to change their marketing strategy. Enterprises must think about how to market with consumers in interaction, let consumers understand company’s brand value and be influenced through interaction, stand out from the huge amount of information to attract consumers' attention, and how to rotate in information, finding effective marketing channels in fast and noisy online communities. In the mentioned research questions, to the best of our knowledge, previous studies major focus on single social media platform. To remedy this research gap, this study proposed a method to find the most influence path of word-of-mouth for marketing that maximize the information diffusion. This method also identifies the key nodes that cause the diffusion benefit from the path to see if there is a specific media or organization that assists the brand owner in operating the word-of-mouth operation business. In the future, enterprises can refer to the results of this study to formulate a word-of-mouth marketing strategy.
Chen, Hsin-Chun, and 陳信君. "Studies on Diffusion Extraction of Soluble Constituents and Volatile Components in Mei (Prunus mume Sieb. et Zucc.) Liqueur during Maceration with Rice Wine." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/92527037420808059514.
Повний текст джерела國立臺灣大學
園藝學研究所
90
This research is to study on diffusion extractions of soluble constituents and volatile components in Mei (Prunus mume Sieb. Et Zucc.) liqueur during maceration with rice wine. Samples were from mei fruit (250g) with different cultivars (Ta-Ching and Yen-Chih), and different ripening (90, 100, 110 days after anthesis) soaked in 35 vol % alcohol with different amount of sugar (150g). The maceration times were 0, 30, 90, 180 and 360 days. Within these days, compositions were regularly sampled and analyzed. Results showed that total soluble solid and pH value were different with cultivars, process and maceration time. However, total phenol and tannin content in mei liqueur increased with the increasing of maceration time. The capacity of the scavenging effect from mei liqueur on DPPH radical was up to 78%. The volatile flavor compounds in the mei liqueur were adsorped by a Amberlite XAD-2 resin and analyzed with GC and GC/MS. Total of thirty compounds were identified, including 11 esters, 7 alcohols, 2 aldehydes, 3 acids and 1 aromatic hydrocarbons compounds. Among the volatile flavor compounds in the mei liqueur, the content of isoamyl alcohol was found with the highest (33.50%), and benzaldehyde was found with the second (21.06%). The comparision of volatile compounds amounts in mei liqueur during the maceration with various mei cultivars harvested after anthesis for various periods was also studied. In the Ta-Ching cultivar, added suger after 180 days on the amounts in mei liqueur during maceration with Ta-Ching mei harvested after anthesis for 90-days was the highest, while Yen-Chih cultivar of added suger after 270 days on the amounts in mei liqueur during maceration with Yen-Chih mei harvested after anthesis for 100-days was the highest.
Meddour, Miriam. "MR-tomographische Darstellung intracerebraler Blutungen mit und ohne Therapie." Doctoral thesis, 2011. http://hdl.handle.net/11858/00-1735-0000-0006-B180-D.
Повний текст джерелаКниги з теми "MRI, Diffusion, MEG"
jia, Fen, and Zeng ying. Mei you dui shou de jing zheng. Bei jing: Qun yan chu ban she, 2008.
Знайти повний текст джерелаJones, PhD, Derek K., ed. Diffusion MRI. Oxford University Press, 2012. http://dx.doi.org/10.1093/med/9780195369779.001.0001.
Повний текст джерелаGlockner, James F., Kazuhiro Kitajima, and Akira Kawashima. Magnetic resonance imaging. Edited by Christopher G. Winearls. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0015_update_001.
Повний текст джерелаDas, Raj, Susan Heenan, and Uday Patel. Magnetic resonance imaging in urology. Edited by Michael Weston. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199659579.003.0134.
Повний текст джерелаKonrad, Kerstin, Adriana Di Martino, and Yuta Aoki. Brain volumes and intrinsic brain connectivity in ADHD. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198739258.003.0006.
Повний текст джерелаBandettini, Peter A., and Hanzhang Lu. Magnetic Resonance Methodologies. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0008.
Повний текст джерелаGorman, Jack M. Brain Imaging. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190850128.003.0005.
Повний текст джерелаCohen-Inbar, Or, Daniel M. Trifiletti, and Jason P. Sheehan. Stereotatic Radiosurgery and Microsurgery for Brain Metastases. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190696696.003.0024.
Повний текст джерелаKrause-Utz, Annegret, Inga Niedtfeld, Julia Knauber, and Christian Schmahl. Neurobiology of Borderline Personality Disorder. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199997510.003.0006.
Повний текст джерелаЧастини книг з теми "MRI, Diffusion, MEG"
Catani, Marco. "The Functional Anatomy of White Matter: From Postmortem Dissections to In Vivo Virtual Tractography." In Diffusion MRI, 5–18. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0001.
Повний текст джерелаFilley, Christopher M. "Neurobiology of White Matter Disorders." In Diffusion MRI, 19–30. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0002.
Повний текст джерелаAxer, Hubertus. "Invasive Methods for Tracing White Matter Architecture." In Diffusion MRI, 31–42. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0003.
Повний текст джерелаCallaghan, Paul T. "Physics of Diffusion." In Diffusion MRI, 45–56. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0004.
Повний текст джерелаLe Bihan, Denis. "Magnetic Resonance Diffusion Imaging: Introduction and Concepts." In Diffusion MRI, 57–78. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0005.
Повний текст джерелаBasser, Peter J., and Evren Özarslan. "Anisotropic Diffusion: From the Apparent Diffusion Coefficient to the Apparent Diffusion Tensor." In Diffusion MRI, 79–91. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0006.
Повний текст джерелаBeaulieu, Christian. "What Makes Diffusion Anisotropic in the Nervous System?" In Diffusion MRI, 92–109. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0007.
Повний текст джерелаAckerman, Joseph J. H., and Jeffrey J. Neil. "Biophysics of Diffusion in Cells." In Diffusion MRI, 110–24. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0008.
Повний текст джерелаCohen, Yoram, and Yaniv Assaf. "Extracting Geometric Properties of White Matter with q-Space Diffusion MRI (QSI)." In Diffusion MRI, 125–51. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0009.
Повний текст джерелаKiselev, Valerij G. "The Cumulant Expansion: An Overarching Mathematical Framework For Understanding Diffusion NMR." In Diffusion MRI, 152–68. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0010.
Повний текст джерелаТези доповідей конференцій з теми "MRI, Diffusion, MEG"
Kojcic, Ivana, Theodore Papadopoulo, Rachid Deriche, and Samuel Deslauriers-Gauthier. "Incorporating Transmission Delays Supported By Diffusion Mri In Meg Source Reconstruction." In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI). IEEE, 2021. http://dx.doi.org/10.1109/isbi48211.2021.9433861.
Повний текст джерелаFukushima, Makoto, Okito Yamashita, Thomas R. Knosche, and Masa-aki Sato. "MEG source reconstruction constrained by diffusion MRI based whole brain dynamical model." In 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013). IEEE, 2013. http://dx.doi.org/10.1109/isbi.2013.6556646.
Повний текст джерелаPhilippe, Anne-Charlotte, Maureen Clerc, Theodore Papadopoulo, and Rachid Deriche. "A nested cortex parcellation combining analysis of MEG forward problem and diffusion MRI tractography." In 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012). IEEE, 2012. http://dx.doi.org/10.1109/isbi.2012.6235599.
Повний текст джерелаBelaoucha, Brahim, Jean-Marc Lina, Maureen Clerc, and Theodore Papadopoulo. "MEM-diffusion MRI framework to solve MEEG inverse problem." In 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE, 2015. http://dx.doi.org/10.1109/eusipco.2015.7362709.
Повний текст джерелаDantas, Pedro da Cunha, Lucas Pablo Almendro, Ana Caroline Fonseca Silva, and André Douglas Marinho da Silva. "Magnetic resonance and its diagnostic accuracy of glioblastoma: narrative review." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.294.
Повний текст джерелаDelgado-Goni, Teresa, Slawomir Wantuch, Teresa Casals-Galobart, Udai Banerji, Nina Tunariu, Simon P. Robinson, Martin O. Leach, and Mounia Beloueche-Babari. "Abstract 4108: Longitudinal diffusion-weighted MRI assessment of NRAS mutant melanoma response to dual RAF-MEK inhibition reveals differences associated with collagen deposition." In Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.am2018-4108.
Повний текст джерелаBeloueche-Babari, Mounia, Yann Jamin, Vaitha Arunan, Simon Walker-Samuel, Paul D. Smith, John C. Waterton, Jane Halliday, Paul Workman, Martin O. Leach, and Simon P. Robinson. "Abstract LB-48: Non-invasive imaging of response to MEK Inhibition with AZD6244 (ARRY-142886) in a human melanoma xenograft monitored by diffusion-weighted MRI." In Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC. American Association for Cancer Research, 2010. http://dx.doi.org/10.1158/1538-7445.am10-lb-48.
Повний текст джерелаDuport, Laurent J. "Georges Candilis (1913-1995) architecte pour le plus grand nombre." In LC2015 - Le Corbusier, 50 years later. Valencia: Universitat Politècnica València, 2015. http://dx.doi.org/10.4995/lc2015.2015.664.
Повний текст джерела