FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

Fluorescence Microscopy Imaging Denoising with Log-Euclidean Priors and Photobleaching Compensation

Fluorescent protein microscopy imaging is nowadays one of the most important tools in biomedical research. However, the resulting images present a low signal to noise ratio and a time intensity decay due to the photobleaching effect. This phenomenon is a consequence of the decreasing on the radiation emission efficiency of the tagging protein. This occurs because the fluorophore permanently loses its ability to fluoresce, due to photochemical reactions induced by the incident light. The Poisson multiplicative noise that corrupts these images, in addition with its quality degradation due to photobleaching, make long time biological observation processes very difficult. In this paper a denoising algorithm for Poisson data, where the photobleaching effect is explicitly taken into account, is described. The algorithm is designed in a Bayesian framework where the data fidelity term models the Poisson noise generation process as well as the exponential intensity decay caused by the photobleaching. The prior term is conceived with Gibbs priors and log-Euclidean potential functions, suitable to cope with the positivity constrained nature of the parameters to be estimated. Monte Carlo tests with synthetic data are presented to characterize the performance of the algorithm. One example with real data is included to illustrate its application.

Radiological imaging in digital systems: the effect of exposure parameters in diagnostic quality and patient dose

Esta tese pretende contribuir para o estudo e análise dos factores relacionados com as técnicas de aquisição de imagens radiológicas digitais, a qualidade diagnóstica e a gestão da dose de radiação em sistema de radiologia digital. A metodologia encontra-se organizada em duas componentes. A componente observacional, baseada num desenho do estudo de natureza retrospectiva e transversal. Os dados recolhidos a partir de sistemas CR e DR permitiram a avaliação dos parâmetros técnicos de exposição utilizados em radiologia digital, a avaliação da dose absorvida e o índice de exposição no detector. No contexto desta classificação metodológica (retrospectiva e transversal), também foi possível desenvolver estudos da qualidade diagnóstica em sistemas digitais: estudos de observadores a partir de imagens arquivadas no sistema PACS. A componente experimental da tese baseou-se na realização de experiências em fantomas para avaliar a relação entre dose e qualidade de imagem. As experiências efectuadas permitiram caracterizar as propriedades físicas dos sistemas de radiologia digital, através da manipulação das variáveis relacionadas com os parâmetros de exposição e a avaliação da influência destas na dose e na qualidade da imagem. Utilizando um fantoma contraste de detalhe, fantomas antropomórficos e um fantoma de osso animal, foi possível objectivar medidas de quantificação da qualidade diagnóstica e medidas de detectabilidade de objectos. Da investigação efectuada, foi possível salientar algumas conclusões. As medidas quantitativas referentes à performance dos detectores são a base do processo de optimização, permitindo a medição e a determinação dos parâmetros físicos dos sistemas de radiologia digital. Os parâmetros de exposição utilizados na prática clínica mostram que a prática não está em conformidade com o referencial Europeu. Verifica-se a necessidade de avaliar, melhorar e implementar um padrão de referência para o processo de optimização, através de novos referenciais de boa prática ajustados aos sistemas digitais. Os parâmetros de exposição influenciam a dose no paciente, mas a percepção da qualidade de imagem digital não parece afectada com a variação da exposição. Os estudos que se realizaram envolvendo tanto imagens de fantomas como imagens de pacientes mostram que a sobreexposição é um risco potencial em radiologia digital. A avaliação da qualidade diagnóstica das imagens mostrou que com a variação da exposição não se observou degradação substancial da qualidade das imagens quando a redução de dose é efectuada. Propõe-se o estudo e a implementação de novos níveis de referência de diagnóstico ajustados aos sistemas de radiologia digital. Como contributo da tese, é proposto um modelo (STDI) para a optimização de sistemas de radiologia digital.

Blue-enhanced thin-film photodiode for dual-screen x-ray imaging

This article reports on a-Si:H-based low-leakage blue-enhanced photodiodes for dual-screen x-ray imaging detectors. Doped nanocrystalline silicon was incorporated in both the n- and p-type regions to reduce absorption losses for light incoming from the top and bottom screens. The photodiode exhibits a dark current density of 900 pA/cm(2) and an external quantum efficiency up to 90% at a reverse bias of 5 V. In the case of illumination through the tailored p-layer, the quantum efficiency of 60% at a 400 nm wavelength is almost double that for the conventional a-Si:H n-i-p photodiode.

Stacked pin Devices for Imaging Applications

In this paper we present results on the optimization of device architectures for colour and imaging applications, using a device with a TCO/pinpi'n/TCO configuration. The effect of the applied voltage on the color selectivity is discussed. Results show that the spectral response curves demonstrate rather good separation between the red, green and blue basic colors. Combining the information obtained under positive and negative applied bias a colour image is acquired without colour filters or pixel architecture. A low level image processing algorithm is used for the colour image reconstruction.

Dynamical behaviour on the parameter space: new populational growth models proportional to beta densities

We present new populational growth models, generalized logistic models which are proportional to beta densities with shape parameters p and 2, where p > 1, with Malthusian parameter r. The complex dynamical behaviour of these models is investigated in the parameter space (r, p), in terms of topological entropy, using explicit methods, when the Malthusian parameter r increases. This parameter space is split into different regions, according to the chaotic behaviour of the models.

Caracterização de regiões encefálicas no cérebro normal por tensor de difusão e aplicação à epilepsia pós-traumática

Mestrado em Radiações Aplicadas às Tecnologias da Saúde.

Digital imaging systems for plain radiography

Advances in digital technology led to the development of digital x-ray detectors that are currently in wide use for projection radiography, including Computed Radiography (CR) and Digital Radiography (DR). Digital Imaging Systems for Plain Radiography addresses the current technological methods available to medical imaging professionals to ensure the optimization of the radiological process concerning image quality and reduction of patient exposure. Based on extensive research by the authors and reference to the current literature, the book addresses how exposure parameters influence the diagnostic quality in digital systems, what the current acceptable radiation doses are for useful diagnostic images, and at what level the dose could be reduced to maintain an accurate diagnosis. The book is a valuable resource for both students learning the field and for imaging professionals to apply to their own practice while performing radiological examinations with digital systems.

Claustrophobia and adherence in magnetic resonance imaging procedure

Claustrophobia causes a huge discomfort to those who need to perform Magnetic Resonance examinations mainly due to the physical design of most equipment. This study aimed to maximize the success rate of Magnetic Resonance Imaging (MRI) clinical studies in claustrophobic patients by the identification of facilitative strategies.

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Short-term Feature Space and Music Genre Classification

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.

Physiologic effect of caffeine on susceptibility-weighted imaging

Susceptibility-weighted imaging (SWI) is a relatively new contrast in MR imaging. Previous studies have found an effect of caffeine in the contrast generated by SWI images. The present study investigates the effect of caffeine on contrast-to-noise ratio (CNR) in SWI.

Seismic imaging of the western Iberian crust using ambient noise: Boundaries and internal structure of the Iberian Massif

We present new Rayleigh-wave dispersion maps of the western Iberian Peninsula for periods between 8 and 30 s, obtained from correlations of seismic ambient noise, following the recent increase in seismic broadband network density in Portugal and Spain. Group velocities have been computed for each station pair using the empirical Green's functions generated by cross-correlating one-day-length seismic ambient-noise records. The resulting high-path density allows us to obtain lateral variations of the group velocities as a function of period in cells of 0.5 degrees x 0.5 degrees with an unprecedented resolution. As a result we were able to address some of the unknowns regarding the lithospheric structure beneath SW Iberia. The dispersion maps allow the imaging of the major structural units, namely the Iberian Massif, and the Lusitanian and Algarve Meso-Cenozoic basins. The Cadiz Gulf/Gibraltar Strait area corresponds to a strong low-velocity anomaly, which can be followed to the largest period inverted, although slightly shifted to the east at longer periods. Within the Iberian Massif, second-order perturbations in the group velocities are consistent with the transitions between tectonic units composing the massif. (C) 2013 Elsevier B.V. All rights reserved.

Molecular imaging agents for detection of β-amyloid plaques in Alzheimer’s disease

The formation of amyloid structures is a neuropathological feature that characterizes several neurodegenerative disorders, such as Alzheimer´s and Parkinson´s disease. Up to now, the definitive diagnosis of these diseases can only be accomplished by immunostaining of post mortem brain tissues with dyes such Thioflavin T and congo red. Aiming at early in vivo diagnosis of Alzheimer´s disease (AD), several amyloid-avid radioprobes have been developed for b-amyloid imaging by positron emission tomography (PET) and single-photon emission computed tomography (SPECT). The aim of this paper is to present a perspective of the available amyloid imaging agents, special those that have been selected for clinical trials and are at the different stages of the US Food and Drugs Administration (FDA) approval.

10 kVp rule – An anthropomorphic pelvis phantom imaging study using a CR system: impact on image quality and effective dose using AEC and manual mode

Purpose - This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose (E) for pelvis using automatic exposure control (AEC) and non-AEC in a Computed Radiography (CR) system. Methods and materials - To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60–120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the two alternative forced choice (2AFC) visual grading software. PCXMC software was used to estimate E. Results - A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p > 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. E results show a statistically significant decrease (p = 0.000) on the 75th quartile from 0.37 mSv at 60 kVp to 0.13 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion - Using the 10 kVp rule, no significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant E reduction is observed.