Search results for "MRI."
showing 10 items of 591 documents
Técnicas de análisis de posproceso en resonancia magnetica parael estudio de la conectividad cerebral
2011
Brain connectivity is a key concept for understanding brain function. Current methods to detect and quantify different types of connectivity with neuroimaging techniques are fundamental for understanding the pathophysiology of many neurologic and psychiatric disorders. This article aims to present a critical review of the magnetic resonance imaging techniques used to measure brain connectivity within the context of the Human Connectome Project. We review techniques used to measure: a) structural connectivity b) functional connectivity (main component analysis, independent component analysis, seed voxel, meta-analysis), and c) effective connectivity (psychophysiological interactions, causal …
Water capillary absorption in porous media in different wettability conditions studied by Quantitative MRI and X-ray CT
2007
X-ray computed tomography (CT) and magnetic resonance imaging (MRI) have been successfully applied to study both the capillary properties of several samples of Lecce stone and the performances of treatments used for protection and conservation of historical stone artifacts. The presence of water inside the sample may be visualized by both MRI and X-ray CT. For the treated samples, the different dynamics of water absorption gives indirectly the efficacy of the polymer in the rock.
Effect of internal noise on the relaxation time of an yttria stabilized zirconia-based memristor
2022
The effects of temperature on the switching kinetics of an yttrium-stabilized zirconia-based memristor from a low-resistance state to a high-resistance state have been experimentally investigated. It was found that the memristor relaxation time depends on the temperature in a non-monotonous way, with a maximum observed at the temperature close to 55 °C. This nonmonotonic behavior is a signature of the noise-enhanced stability phenomenon observed in all physical and complex systems characterized by metastable states.
A classification approach to prostate cancer localization in 3T Multi-Parametric MRI
2016
International audience; Multiparametric-magnetic resonance imaging (mp-MRI) has demonstrated, in many studies, its potential in prostate cancer detection and analysis. We propose a supervised classification approach based on mp-MRI data base of 20 patients, in order to localize prostate cancer and to achieve a cartographic representation of the prostate voxels based on classification results. Proposed method provides a computer aided detection (CAD) software for prostatic cancer. For that, we have extracted varied features providing functional, anatomical and metabolic information helping the classifier to distinguish between three different classes ("Healthy", "Benign" and "Pathologic"). W…
Definition of a mutual reference shape based on information theory and active contours
2013
In this paper, we propose to consider the estimation of a reference shape from a set of different segmentation results using both active contours and information theory. The reference shape is then defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations. This energy criterion is here justified using similarities between information theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the specificity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each te…
Leveraging Uncertainty Estimates to Improve Segmentation Performance in Cardiac MR
2021
International audience; In medical image segmentation, several studies have used Bayesian neural networks to segment and quantify the uncertainty of the images. These studies show that there might be an increased epistemic uncertainty in areas where there are semantically and visually challenging pixels. The uncertain areas of the image can be of a great interest as they can possibly indicate the regions of incorrect segmentation. To leverage the uncertainty information, we propose a segmentation model that incorporates the uncertainty into its learning process. Firstly, we generate the uncertainty estimate (sample variance) using Monte-Carlo dropout during training. Then we incorporate it …
Using Polynomial Loss and Uncertainty Information for Robust Left Atrial and Scar Quantification and Segmentation
2022
Automatic and accurate segmentation of the left atrial (LA) cavity and scar can be helpful for the diagnosis and prognosis of patients with atrial fibrillation. However, automating the segmentation can be difficult due to the poor image quality, variable LA shapes, and small discrete regions of LA scars. In this paper, we proposed a fully-automatic method to segment LA cavity and scar from Late Gadolinium Enhancement (LGE) MRIs. For the loss functions, we propose two different losses for each task. To enhance the segmentation of LA cavity from the multicenter dataset, we present a hybrid loss that leverages Dice loss with a polynomial version of cross-entropy loss (PolyCE). We also utilize …
Qauntum control of molecular rotation and of processes in Nuclear Magnetic Resonance
2019
The goal of this thesis is to apply quantum control techniques to manipulate molecular rotation and to enhance the efficiency of processes in Nuclear Magnetic Resonance.These techniques have been used theoretically and experimentally to control the orientation of a symmetric top molecule by means of THz laser fields. This study has been extended to the case of a long interaction distance between the field and the sample. In this case, the molecule cannot be approximated as isolated. We have also shown the extend to which the time evolution of the degree of orientation can be shaped. Optimal control techniques were used to design the THz field which allows to reach the corresponding dynamics…
Impact of sweet food consumption on children's brain responses to sweet taste: a functional imaging study
2014
National audience
Brain networks activated during sweet taste processing in children: an fMRI study
2017
International audience