Ricardo E. de Souza

Manganese-enhanced magnetic resonance imaging (MEMRI) of rat brain after systemic administration of MnCl2: Changes in T1 relaxation times during postnatal development

To measure regional T1 changes in the postnatal rat brain following systemic administration of the contrast agent manganese chloride (MnCl2).

Evaluation of Alzheimer's disease by analysis of MR images using Objective Dialectical Classifiers as an alternative to 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 (DW) 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 Objective Dialectical Classifiers, a new method based on Dialectics as defined in the Philosophy of Praxis. A 2-degree polynomial network with supervised training is used to generate the ground truth image. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map.

Evaluation of Alzheimer's disease by analysis of MR images using multilayer perceptrons and committee machines.

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 its correlation with the advance of Alzheimers disease. The MR images were acquired from a unique volunteer with Alzheimers, using an image system based on a clinical 1.5T tomographer. The classification methods are based on multilayer perceptrons and committee machines and the classification results are used to correlate clinical and imaging findings. The classification results are used to improve the usual analysis of the ADC map.

Avaliação Da Doença De Alzheimer Pela Análise Multiespectral De Imagens DW-MR Por Redes BRF Como Alternativa Aos Mapas ADC

Alzheimers disease is the most common cause of dementia, yet difficult to accurately diagnose without the use of invasive techniques, particularly at the beginning of the disease. This work addresses the classification and analysis of multispectral synthetic images composed by diffusion-weighted magnetic resonance brain volumes for evaluation of the area of cerebrospinal fluid and its correlation with the progression of Alzheimers disease. A 1.5 T MR imaging system was used to acquire all the images presented. The classification methods are based on multilayer perceptrons and classifiers of radial basis function networks. It is assumed that the classes of interest can be separated by hyperquadrics. A polynomial network of degree 2 is used to classify the original volumes, generating a ground-truth volume. The classification results are used to improve the usual analysis by the map of apparent diffusion coefficients.

Reconstruction of electrical impedance tomography images using genetic algorithms and non-blind search

The development and improvement of non-invasive imaging techniques have been increasing in the last decades, due to interests from both academy and industry. Electrical Impedance Tomography (EIT) is a noninvasive imaging technique that offers a vast field of possibilities due to its low cost, portability, and safety of handling. However, EIT image reconstruction is an ill-posed problem. Herein this work we present an EIT reconstruction method based on the optimization of the relative error of reconstruction using genetic algorithms employing elitist strategies. The initial set of solutions used by the elitist genetic algorithm includes a noisy version of the solution obtained from the backprojection algorithm, according to Saha and Bandyopadhyays criterion for non-blind initial search in optimization algorithms, in order to accelerate convergence and improve performance.

FPGA-based digital direct-conversion transceiver for Nuclear Magnetic Resonance Systems

Direct-conversion is an alternative to the established superheterodyne architecture for Nuclear Magnetic Resonance (NMR) transceivers. In this work, a digital direct-conversion transceiver for NMR is described. Following a software-defined radio paradigm, all signal processing tasks - including down-conversion to baseband - are performed in the digital domain, without analog heterodyning at the transceiver front-end. A programmable NMR pulse programmer with a minimum resolution of 24 ns is also integrated in the transceiver design, which allows the execution of user-defined pulse sequences. The RF Transceiver architecture is implemented in an Altera Cyclone II FPGA, and described in the VHDL hardware description language. The proposed architecture is suited for compact, low-cost NMR systems, for education and research, and is capable to perform experiments in areas such as NMR spectroscopy and relaxometry.

Dialectical multispectral classification of diffusion-weighted magnetic resonance images as an alternative to apparent diffusion coefficients maps to perform anatomical analysis

Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. 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): a method for classification based on the philosophy of praxis. ODM is instrumental in assembling evolvable mathematical tools to analyze multispectral images. In the case study described in this paper, 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. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map. Such results proved that gray and white matter can be distinguished in DW-MR multispectral analysis and, consequently, DW-MR images can also be used to furnish anatomical information.

A monospectral approach for fMRI analysis using Kohonen self-organised networks and objective dialectical classifiers

One of the major challenges at the field of cognitive sciences is mapping the regions of the brain responsible for the motor and behavioural functions. The acquisition of functional magnetic resonance images is an important non-invasive technique to study the neural activity in the human brain. The dialectical conception of reality is a kind of philosophical investigative method for analysing processes present in nature and in human societies. The dialectical method is a tool for studying systems by considering the dynamics of their contradictions, as dynamic processes with intertwined phases of evolution and revolutionary crisis. It has inspired us to conceive a dialectical classifier able to solve classification problems. 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 a non-parametrical method based on Kohonen self-organised networks and in objective dialectical classifiers.

Evaluation of Alzheimer's disease by analysis of MR images using multilayer perceptrons, polynomial nets and Kohonen LVQ classifiers

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 its correlation with the advance of Alzheimers 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, polynomial nets and Kohonen LVQ classifiers. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map.

Nuclear magnetic resonance study of proton exchanged LiNbO3

Nuclear magnetic resonance (NMR) of 1H was employed to study the population of different sites in proton exchanged LiNbO3 using a variety of exchange conditions and proton donors. At least two different proton sites of vastly different mobilities were always found to be present. The ratio of their populations was measured in annealed and as‐prepared samples and found to be strongly dependent upon the exchange conditions. A correlation between our NMR data and recent results obtained using other techniques is discussed in connection with various mechanisms that have been proposed for the changes in the refractive indexes.