keyword
MENU ▼
Read by QxMD icon Read
search

Dmri

keyword
https://www.readbyqxmd.com/read/28367515/shared-microstructural-features-of-behavioral-and-substance-addictions-revealed-in-areas-of-crossing-fibers
#1
Sarah W Yip, Kristen P Morie, Jiansong Xu, R Todd Constable, Robert T Malison, Kathleen M Carroll, Marc N Potenza
BACKGROUND: Similarities between behavioral and substance addictions exist. However, direct neurobiological comparison between addictive disorders is rare. Determination of disorder-specificity (or lack thereof) of alterations within white-matter microstructures will advance understanding of the pathophysiology of addictions. METHODS: We compared white-matter microstructural features between individuals with gambling disorder (GD; n=38), cocaine-use disorder (CUD; n=38) and healthy comparison (HC; n=38) participants, as assessed using diffusion-weighted magnetic resonance imaging (dMRI)...
March 2017: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
https://www.readbyqxmd.com/read/28275542/parkinson-s-disease-diffusion-mri-is-not-affected-by-acute-antiparkinsonian-medication
#2
Jae Woo Chung, Roxana G Burciu, Edward Ofori, Priyank Shukla, Michael S Okun, Christopher W Hess, David E Vaillancourt
OBJECTIVE: A prior longitudinal study demonstrates that free-water diffusion magnetic resonance imaging (dMRI) tracks progression in the substantia nigra (Ofori et al., 2015b). Here, we test the acute effects of antiparkinsonian medication on this established imaging progression marker for the first time. METHODS: Fifteen PD patients underwent dMRI OFF and ON-medication one day apart. ON-medication, patients were tested approximately 45 min after their usual dose of antiparkinsonian medication...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28272771/sensitivity-of-diffusion-mri-to-perilesional-reactive-astrogliosis-in-focal-ischemia
#3
Rachel A Weber, Clifford H Chan, Xingju Nie, Emily Maggioncalda, Grace Valiulis, Abigail Lauer, Edward S Hui, Jens H Jensen, DeAnna L Adkins
Reactive astrogliosis is a response to injury in the central nervous system that plays an essential role in inflammation and tissue repair. It is characterized by hypertrophy of astrocytes, alterations in astrocyte gene expression and astrocyte proliferation. Reactive astrogliosis occurs in multiple neuropathologies, including stroke, traumatic brain injury and Alzheimer's disease, and it has been proposed as a possible source of the changes in diffusion magnetic resonance imaging (dMRI) metrics observed with these diseases...
March 8, 2017: NMR in Biomedicine
https://www.readbyqxmd.com/read/28271301/mechanisms-of-circumferential-gyral-convolution-in-primate-brains
#4
Tuo Zhang, Mir Jalil Razavi, Hanbo Chen, Yujie Li, Xiao Li, Longchuan Li, Lei Guo, Xiaoping Hu, Tianming Liu, Xianqiao Wang
Mammalian cerebral cortices are characterized by elaborate convolutions. Radial convolutions exhibit homology across primate species and generally are easily identified in individuals of the same species. In contrast, circumferential convolutions vary across species as well as individuals of the same species. However, systematic study of circumferential convolution patterns is lacking. To address this issue, we utilized structural MRI (sMRI) and diffusion MRI (dMRI) data from primate brains. We quantified cortical thickness and circumferential convolutions on gyral banks in relation to axonal pathways and density along the gray matter/white matter boundaries...
March 7, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28269176/multivariate-autoregressive-model-constrained-by-anatomical-connectivity-to-reconstruct-focal-sources
#5
Brahim Belaoucha, Mouloud Kachouane, Theodore Papadopoulo
In this paper, we present a framework to reconstruct spatially localized sources from Magnetoencephalography (MEG)/Electroencephalography (EEG) using spatiotemporal constraint. The source dynamics are represented by a Multivariate Autoregressive (MAR) model whose matrix elements are constrained by the anatomical connectivity obtained from diffusion Magnetic Resonance Imaging (dMRI). The framework assumes that the whole brain dynamic follows a constant MAR model in a time window of interest. The source activations and the MAR model parameters are estimated iteratively...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269167/supervised-multimodal-fusion-and-its-application-in-searching-joint-neuromarkers-of-working-memory-deficits-in-schizophrenia
#6
Shile Qi, Vince D Calhoun, Theo G M van Erp, Eswar Damaraju, Juan Bustillo, Yuhui Du, Jessica A Turner, Daniel H Mathalon, Judith M Ford, James Voyvodic, Bryon A Mueller, Aysenil Belger, Sarah McEwen, Steven G Potkin, Adrian Preda, F Birn, Tianzi Jiang, Jing Sui
Multimodal fusion is an effective approach to better understand brain disease. To date, most current fusion approaches are unsupervised; there is need for a multivariate method that can adopt prior information to guide multimodal fusion. Here we proposed a novel supervised fusion model, called "MCCAR+jICA", which enables both identification of multimodal co-alterations and linking the covarying brain regions with a specific reference signal, e.g., cognitive scores. The proposed method has been validated on both simulated and real human brain data...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268809/automated-tracking-segmentation-and-trajectory-classification-of-pelvic-organs-on-dynamic-mri
#7
Iman Nekooeimehr, Susana Lai-Yuen, Paul Bao, Alfredo Weitzenfeld, Stuart Hart
Pelvic organ prolapse is a major health problem in women where pelvic floor organs (bladder, uterus, small bowel, and rectum) fall from their normal position and bulge into the vagina. Dynamic Magnetic Resonance Imaging (DMRI) is presently used to analyze the organs' movements from rest to maximum strain providing complementary support for diagnosis. However, there is currently no automated or quantitative approach to measure the movement of the pelvic organs and their correlation with the severity of prolapse...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268520/multi-output-gaussian-processes-for-enhancing-resolution-of-diffusion-tensor-fields
#8
Hernan Dario Vargas Cardona, Alvaro A Orozco, Mauricio A Alvarez
Second order diffusion tensor (DT) fields are widely used in several clinical applications: brain fibers connections, diagnosis of neuro-degenerative diseases, image registration, brain conductivity models, etc. However, due to current acquisition protocols and hardware limitations in MRI machines, the diffusion magnetic resonance imaging (dMRI) data is obtained with low spatial resolution (1 or 2 mm3 for each voxel). This issue can be significant, because tissue fibers are much smaller than voxel size. Interpolation has become in a successful methodology for enhancing spatial resolution of DT fields...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28266059/fractional-anisotropy-derived-from-the-diffusion-tensor-distribution-function-boosts-power-to-detect-alzheimer-s-disease-deficits
#9
Talia M Nir, Neda Jahanshad, Julio E Villalon-Reina, Dmitry Isaev, Artemis Zavaliangos-Petropulu, Liang Zhan, Alex D Leow, Clifford R Jack, Michael W Weiner, Paul M Thompson
PURPOSE: In diffusion MRI (dMRI), fractional anisotropy derived from the single-tensor model (FA(DTI) ) is the most widely used metric to characterize white matter (WM) microarchitecture, despite known limitations in regions with crossing fibers. Due to time constraints when scanning patients in clinical settings, high angular resolution diffusion imaging acquisition protocols, often used to overcome these limitations, are still rare in clinical population studies. However, the tensor distribution function (TDF) may be used to model multiple underlying fibers by representing the diffusion profile as a probabilistic mixture of tensors...
March 7, 2017: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
https://www.readbyqxmd.com/read/28227406/multivariate-autoregressive-model-constrained-by-anatomical-connectivity-to-reconstruct-focal-sources
#10
Brahim Belaoucha, Mouloud Kachouane, Theodore Papadopoulo, Brahim Belaoucha, Mouloud Kachouane, Theodore Papadopoulo, Brahim Belaoucha, Theodore Papadopoulo, Mouloud Kachouane
In this paper, we present a framework to reconstruct spatially localized sources from Magnetoencephalography (MEG)/Electroencephalography (EEG) using spatiotemporal constraint. The source dynamics are represented by a Multivariate Autoregressive (MAR) model whose matrix elements are constrained by the anatomical connectivity obtained from diffusion Magnetic Resonance Imaging (dMRI). The framework assumes that the whole brain dynamic follows a constant MAR model in a time window of interest. The source activations and the MAR model parameters are estimated iteratively...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227396/supervised-multimodal-fusion-and-its-application-in-searching-joint-neuromarkers-of-working-memory-deficits-in-schizophrenia
#11
Shile Qi, Vince D Calhoun, Theo G M van Erp, Eswar Damaraju, Juan Bustillo, Yuhui Du, Jessica A Turner, Daniel H Mathalon, Judith M Ford, James Voyvodic, Bryon A Mueller, Aysenil Belger, Sarah Mc Ewen, Steven G Potkin, Adrian Preda, F Birn, Tianzi Jiang, Jing Sui, Shile Qi, Vince D Calhoun, Theo G M van Erp, Eswar Damaraju, Juan Bustillo, Yuhui Du, Jessica A Turner, Daniel H Mathalon, Judith M Ford, James Voyvodic, Bryon A Mueller, Aysenil Belger, Sarah McEwen, Steven G Potkin, Adrian Preda, F Birn, Tianzi Jiang, Jing Sui
Multimodal fusion is an effective approach to better understand brain disease. To date, most current fusion approaches are unsupervised; there is need for a multivariate method that can adopt prior information to guide multimodal fusion. Here we proposed a novel supervised fusion model, called "MCCAR+jICA", which enables both identification of multimodal co-alterations and linking the covarying brain regions with a specific reference signal, e.g., cognitive scores. The proposed method has been validated on both simulated and real human brain data...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227004/automated-tracking-segmentation-and-trajectory-classification-of-pelvic-organs-on-dynamic-mri
#12
Iman Nekooeimehr, Susana Lai-Yuen, Paul Bao, Alfredo Weitzenfeld, Stuart Hart, Iman Nekooeimehr, Susana Lai-Yuen, Paul Bao, Alfredo Weitzenfeld, Stuart Hart, Paul Bao, Susana Lai-Yuen, Stuart Hart, Alfredo Weitzenfeld, Iman Nekooeimehr
Pelvic organ prolapse is a major health problem in women where pelvic floor organs (bladder, uterus, small bowel, and rectum) fall from their normal position and bulge into the vagina. Dynamic Magnetic Resonance Imaging (DMRI) is presently used to analyze the organs' movements from rest to maximum strain providing complementary support for diagnosis. However, there is currently no automated or quantitative approach to measure the movement of the pelvic organs and their correlation with the severity of prolapse...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226694/multi-output-gaussian-processes-for-enhancing-resolution-of-diffusion-tensor-fields
#13
Hernan Dario Vargas Cardona, Alvaro A Orozco, Mauricio A Alvarez, Hernan Dario Vargas Cardona, Alvaro A Orozco, Mauricio A Alvarez, Hernan Dario Vargas Cardona, Mauricio A Alvarez, Alvaro A Orozco
Second order diffusion tensor (DT) fields are widely used in several clinical applications: brain fibers connections, diagnosis of neuro-degenerative diseases, image registration, brain conductivity models, etc. However, due to current acquisition protocols and hardware limitations in MRI machines, the diffusion magnetic resonance imaging (dMRI) data is obtained with low spatial resolution (1 or 2 mm(3) for each voxel). This issue can be significant, because tissue fibers are much smaller than voxel size. Interpolation has become in a successful methodology for enhancing spatial resolution of DT fields...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28214787/sparse-and-dense-hybrid-representation-via-subspace-modeling-for-dynamic-mri
#14
Qiegen Liu, Shanshan Wang, Dong Liang
Recent theoretical results on compressed sensing and low-rank matrix recovery have inspired significant interest in joint sparse and low rank modeling of dynamic magnetic resonance imaging (dMRI). Existing approaches usually describe these two respective prior information with different formulations. In this paper, we present a novel sparse and dense hybrid representation (SDR) model which describes the sparse plus low rank properties by a unified way. More specifically, under the learned dictionary consisting of temporal basis functions, SDR models the spatial coefficients in two subspaces with Laplacian and Gaussian prior distributions, respectively...
February 5, 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/28203748/geometric-navigation-of-axons-in-a-cerebral-pathway-comparing-dmri-with-tract-tracing-and-immunohistochemistry
#15
Farzad Mortazavi, Adrian L Oblak, Will Z Morrison, Jeremy D Schmahmann, H Eugene Stanley, Van J Wedeen, Douglas L Rosene
No abstract text is available yet for this article.
February 16, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28180075/independent-value-added-by-diffusion-mri-for-prediction-of-cognitive-function-in-older-adults
#16
Julia A Scott, Duygu Tosun, Meredith N Braskie, Pauline Maillard, Paul M Thompson, Michael Weiner, Charles DeCarli, Owen T Carmichael
The purpose of this study was to determine whether white matter microstructure measured by diffusion magnetic resonance imaging (dMRI) provides independent information about baseline level or change in executive function (EF) or memory (MEM) in older adults with and without cognitive impairment. Longitudinal data was acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study from phases GO and 2 (2009-2015). ADNI participants included were diagnosed as cognitively normal (n = 46), early mild cognitive impairment (MCI) (n = 48), late MCI (n = 29), and dementia (n = 39) at baseline...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28176263/multi-site-harmonization-of-diffusion-mri-data-in-a-registration-framework
#17
Hengameh Mirzaalian, Lipeng Ning, Peter Savadjiev, Ofer Pasternak, Sylvain Bouix, Oleg Michailovich, Sarina Karmacharya, Gerald Grant, Christine E Marx, Rajendra A Morey, Laura A Flashman, Mark S George, Thomas W McAllister, Norberto Andaluz, Lori Shutter, Raul Coimbra, Ross D Zafonte, Mike J Coleman, Marek Kubicki, Carl-Fredrik Westin, Murray B Stein, Martha E Shenton, Yogesh Rathi
Diffusion MRI (dMRI) data acquired on different scanners varies significantly in its content throughout the brain even if the acquisition parameters are nearly identical. Thus, proper harmonization of such data sets is necessary to increase the sample size and thereby the statistical power of neuroimaging studies. In this paper, we present a novel approach to harmonize dMRI data (the raw signal, instead of dMRI derived measures such as fractional anisotropy) using rotation invariant spherical harmonic (RISH) features embedded within a multi-modal image registration framework...
February 7, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28092972/tracking-dynamic-interactions-between-structural-and-functional-connectivity-a-tms-eeg-dmri-study
#18
Enrico Amico, Olivier Bodart, Mario Rosanova, Olivia Gosseries, Lizette Heine, Pieter Van Mierlo, Charlotte Martial, Marcello Massimini, Daniele Marinazzo, Steven Laureys
Transcranial magnetic stimulation (TMS) in combination with neuroimaging techniques allows to measure the effects of a direct perturbation of the brain. When coupled with high-density electroencephalography (TMS/hd-EEG), TMS pulses revealed electrophysiological signatures of different cortical modules in health and disease. However, the neural underpinnings of these signatures remain unclear. Here, by applying multimodal analyses of cortical response to TMS recordings and diffusion magnetic resonance imaging (dMRI) tractography, we investigated the relationship between functional and structural features of different cortical modules in a cohort of awake healthy volunteers...
March 2017: Brain Connectivity
https://www.readbyqxmd.com/read/28072384/impact-of-cerebellar-atrophy-on-cortical-gray-matter-and-cerebellar-peduncles-as-assessed-by-voxel-based-morphometry-and-high-angular-resolution-diffusion-imaging
#19
Michael Dayan, G Olivito, M Molinari, Mara Cercignani, Marco Bozzali, M Leggio
In recent years the cerebellum has been attributed amore important role in higher-level functions than previously believed. We examined a cohort of patients suffering from cerebellar atrophy resulting in ataxia, with two main objectives: first to investigate which regions of the cerebrum were affected by the cerebellar degeneration, and second to assess whether diffusion magnetic resonance imaging (dMRI) metrics within the medial (MCP) and superior cerebellar peduncle (SCP) - namely fractional anisotropy (FA) and radial diffusivity (RD) - could be used as a biomarker in patients with this condition...
October 2016: Functional Neurology
https://www.readbyqxmd.com/read/27994537/alignment-of-tractograms-as-graph-matching
#20
Emanuele Olivetti, Nusrat Sharmin, Paolo Avesani
The white matter pathways of the brain can be reconstructed as 3D polylines, called streamlines, through the analysis of diffusion magnetic resonance imaging (dMRI) data. The whole set of streamlines is called tractogram and represents the structural connectome of the brain. In multiple applications, like group-analysis, segmentation, or atlasing, tractograms of different subjects need to be aligned. Typically, this is done with registration methods, that transform the tractograms in order to increase their similarity...
2016: Frontiers in Neuroscience
keyword
keyword
106338
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"