R.E. de Souza

The limitations of a target field approach to coil design

The limitations of a recently proposed target field approach for the design of solenoidal magnets with highly uniform fields over large volumes are examined. Numerical results of the uniformities attainable and the corresponding current distributions are presented.

Structural determination of hydrogen site occupation in proton‐exchanged LiNbO3 by nuclear magnetic resonance

1H nuclear magnetic resonance measurements in proton‐exchanged LiNbO3 were employed to determine structural positions of sites believed to be responsible for the desirable optical properties of this material. Contributions from other proton sites were first subtracted from the line shape which was subsequently analyzed by Van Vleck’s second moment method using a spin‐echo technique to separate like‐spin from unlike‐spin contributions. Among various models examined, only one in which protons are located on oxygen planes nearest to normal lithium sites, midway between two oxygen anions in an oxygen triangle, was found to be consistent with the data.

Structural properties of crumpled cream layers

The cream layer is a complex heterogeneous material of biological origin which forms spontaneously at the air–milk interface. Here, the crumpling of a single cream layer packing under its own weight at room temperature in a three-dimensional space is studied. The structure obtained in these circumstances has a low volume fraction and anomalous fractal dimensions. Direct means and noninvasive NMR imaging techniques are used to investigate the internal and the external structures of these systems.

Digital NMR imaging system for ultralow magnetic fields

A low-cost, full-body, ultralow magnetic NMR imaging system employing digital detection and RF synthesis is described. The data processing, which involves analogue to digital conversion at the Larmor rate of 680 kHz, followed by digital quadrature detection and digital smoothing with undersampling, is analysed. The performance of the system exhibits significant improvements over more conventional systems operating at ultralow magnetic fields.

A simple, ultralow magnetic field NMR imaging system

The construction of a simple, low-cost NMR imaging system including a 0.3 m diameter electromagnet is described. The system operates at the unusually low frequency of 680 kHz and can be readily scaled-up to a full body machine. In spite of the inherently poor signal-to-noise ratio at this frequency, potentially useful results may be obtained using very simple and inexpensive equipment and a home-built approach.

Evaluation of Alzheimer's Disease by Analysis of MR Images using Multilayer Perceptrons and Kohonen SOM Classifiers as an Alternative to the ADC Maps

Alzheimers disease is the most common cause of dementia, yet hard to diagnose precisely without invasive techniques, particularly at the onset of the disease. This work approaches image analysis and classification of synthetic multispectral images composed by diffusion-weighted magnetic resonance (MR) cerebral images for the evaluation of cerebrospinal fluid area and measuring the advance of Alzheimers disease. A clinical 1.5 T MR imaging system was used to acquire all images presented. The classification methods are based on multilayer perceptrons and Kohonen self-organized map classifiers. We assume the classes of interest can be separated by hyperquadrics. Therefore, a 2-degree polynomial network is used to classify the original image, generating the ground truth image. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map.

A dialectical approach for classification of DW-MR Alzheimer’s images

Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. However, a considerable number of current methods of analysis are based on parametric statistics. Alternatively, some methods in computational intelligence are inspired by biology and other sciences. Here we claim that philosophy can be also considered as a source of inspiration. This work proposes the objective dialectical method (ODM), which is a computational intelligent method for classification based on the philosophy of praxis. Here, ODM is instrumental in assembling evolvable mathematical tools to analyze multispectral images. In the case study described in this paper, such multispectral images are composed of diffusion weighted (DW) magnetic resonance (MR) images. The results are compared to ground-truth images produced by polynomial networks using a morphological similarity index.

Avaliação da Doença de Alzheimer pela Análise Multiespectral de Imagens DW-MR por Mapas Auto-Organizados de Kohonen como Alternativa aos Mapas ADC

Alzheimer’s disease is the most common cause of dementia, yet hard to diagnose precisely without invasive techniques, particularly at the onset of the disease. This work approaches image analysis and classification of synthetic multispectral images composed by diffusion-weighted magnetic resonance (DW-MR) cerebral images for the evaluation of cerebrospinal fluid area and its correlation with the advance of Alzheimer’s disease. The MR images were acquired from an image system by a clinical 1.5 T tomographer. The classification methods are based on multilayer perceptrons and Kohonen self-organized maps. The classification results are used as an alternative to the usual analysis of the ADC map.

Ultralow field Overhauser images of calcium alginate gel formation

We present magnetic resonance images of the formation of an alginate gel as calcium ions diffuse, through a dialysis membrane, into a sodium alginate solution. Instead of conventional magnetic resonance imaging in a high magnetic field, we employed the electronic Overhauser effect in an imaging mode to enhance the proton signal at a field of only 16 mT. The high sensitivity of the Overhauser effect to small changes in mobility permits to monitor spatial inhomogeneity in the very early stages of the gelling process.

A Monospectral Approach for fMRI Analysis using Kohonen Self-Organized Networks

One of the major challenges at the field of cognitive sciences is mapping the regions of the brain responsible for the motor and behavioral functions. The acquisition of functional magnetic resonance images is an important noninvasive technique to study the neural activity in the human brain. This work presents a new approach for the detection of activated brain regions: the composition and analysis of synthetic multi and monospectral images using statistical methods and proposing non-parametrical methods based on Kohonen self-organized networks.