Search results for "MRI."

Adaptive independent vector analysis for multi-subject complex-valued fMRI data.

2017

Abstract Background Complex-valued fMRI data can provide additional insights beyond magnitude-only data. However, independent vector analysis (IVA), which has exhibited great potential for group analysis of magnitude-only fMRI data, has rarely been applied to complex-valued fMRI data. The main challenges in this application include the extremely noisy nature and large variability of the source component vector (SCV) distribution. New method To address these challenges, we propose an adaptive fixed-point IVA algorithm for analyzing multiple-subject complex-valued fMRI data. We exploited a multivariate generalized Gaussian distribution (MGGD)- based nonlinear function to match varying SCV dis…

Three-dimensional architecture of the whole human soleus muscle in vivo

2018

Background Most data on the architecture of the human soleus muscle have been obtained from cadaveric dissection or two-dimensional ultrasound imaging. We present the first comprehensive, quantitative study on the three-dimensional anatomy of the human soleus muscle in vivo using diffusion tensor imaging (DTI) techniques. Methods We report three-dimensional fascicle lengths, pennation angles, fascicle curvatures, physiological cross-sectional areas and volumes in four compartments of the soleus at ankle joint angles of 69 ± 12° (plantarflexion, short muscle length; average ± SD across subjects) and 108 ± 7° (dorsiflexion, long muscle length) of six healthy young adults. Microdissection and…

Evaluation of lumbar pain with weight-bearing MRI: Preliminary experience.

2010

Purpose Methods and Materials Results Conclusion References Personal Information

MR imaging of entrapment neuropathies of the shoulder

2010

Learning objectives Background Imaging findings OR Procedure details Conclusion Personal Information References

Deep learning architectures for automatic detection of viable myocardiac segments

2021

Thesis abstract: Deep learning architectures for automatic detection of viable myocardiac segmentsAccurate myocardial segmentation in LGE-MRI is an important purpose for diagnosis assistance of infarcted patients. Nevertheless, manual delineation of target volumes is time-consuming and depends on intra- and inter-observer variability. This thesis aims at developing efficient deep learning-based methods for automatically segmenting myocardial tissues (healthy myocardium, myocardial infarction, and microvascular obstruction) on LGE-MRI. In this regard, we first proposed a 2.5D SegU-Net model based on a fusion framework (U-Net and SegNet) to learn different feature representations adaptively. …

Elaboration of functionalized nanoparticles : applications as MRI contrast agent

2010

Spinel structured iron oxide nanoparticles open the way of biomedical applications of nanomaterials.Superparamagnetic properties of ten nanometer size crystallites permit to use them in diagnosis such as Magnetic Resonance Imaging (MRI).The aim of this work was to synthesize colloidal suspension of magnetite or maghemite (called USPIO for Ultrasmall SuperParamagnetic Iron Oxide) stable in physiological conditions (pH = 7.4 and [NaCl] = 0.15M).By classical co-precipitation method, UPSIO were synthesized with a mean crystallite size of 8 nm, with a specific surface area of 110 m².g-1 and an aggregate size of 20 nm. To stabilize these nano-objects, two ways were investigated. Electrostatic age…

Supramodal neural processing of abstract information conveyed by speech and gesture

2013

Abstractness and modality of interpersonal communication have a considerable impact on comprehension. They are relevant for determining thoughts and constituting internal models of the environment. Whereas concrete object-related information can be represented in mind irrespective of language, abstract concepts require a representation in speech. Consequently, modality-independent processing of abstract information can be expected. Here we investigated the neural correlates of abstractness (abstract vs. concrete) and modality (speech vs. gestures), to identify an abstractness-specific supramodal neural network. During fMRI data acquisition 20 participants were presented with videos of an ac…

2014

Due to its millisecond-scale temporal resolution, EEG allows to assess neural correlates with precisely defined temporal relationship relative to a given event. This knowledge is generally lacking in data from functional magnetic resonance imaging (fMRI) which has a temporal resolution on the scale of seconds so that possibilities to combine the two modalities are sought. Previous applications combining event-related potentials (ERPs) with simultaneous fMRI BOLD generally aimed at measuring known ERP components in single trials and correlate the resulting time series with the fMRI BOLD signal. While it is a valuable first step, this procedure cannot guarantee that variability of the chosen …

The obsessions of the green-eyed monster: jealousy and the female brain

2019

The present brain-imaging study assessed neural correlates of romantic jealousy in women who had suffered real infidelity by their partner. We predicted to find activation across different brain st...

Resting-state EEG reveals four subphenotypes of amyotrophic lateral sclerosis

2021

Abstract Amyotrophic lateral sclerosis is a devastating disease characterized primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. Amyotrophic lateral sclerosis is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulbar or spinal), burden of disease (based on the modified El Escorial Research Criteria) and genomics in those with familial disease. However, with the exception of genomics, these subcategories do not take into account underlying disease pathobiology, and are not fully predictive of disease course or prognosis. Recently…