Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Parallel hyperspectral coded aperture for compressive sensing on GPUs

The application of compressive sensing (CS) to hyperspectral images is an active area of research over the past few years, both in terms of the hardware and the signal processing algorithms. However, CS algorithms can be computationally very expensive due to the extremely large volumes of data collected by imaging spectrometers, a fact that compromises their use in applications under real-time constraints. This paper proposes four efficient implementations of hyperspectral coded aperture (HYCA) for CS, two of them termed P-HYCA and P-HYCA-FAST and two additional implementations for its constrained version (CHYCA), termed P-CHYCA and P-CHYCA-FAST on commodity graphics processing units (GPUs). HYCA algorithm exploits the high correlation existing among the spectral bands of the hyperspectral data sets and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. The proposed P-HYCA and P-CHYCA implementations have been developed using the compute unified device architecture (CUDA) and the cuFFT library. Moreover, this library has been replaced by a fast iterative method in the P-HYCA-FAST and P-CHYCA-FAST implementations that leads to very significant speedup factors in order to achieve real-time requirements. The proposed algorithms are evaluated not only in terms of reconstruction error for different compressions ratios but also in terms of computational performance using two different GPU architectures by NVIDIA: 1) GeForce GTX 590; and 2) GeForce GTX TITAN. Experiments are conducted using both simulated and real data revealing considerable acceleration factors and obtaining good results in the task of compressing remotely sensed hyperspectral data sets.

Parallel method for sparse semisupervised hyperspectral unmixing

Parallel hyperspectral unmixing problem is considered in this paper. A semisupervised approach is developed under the linear mixture model, where the abundance's physical constraints are taken into account. The proposed approach relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. Since Libraries are potentially very large and hyperspectral datasets are of high dimensionality a parallel implementation in a pixel-by-pixel fashion is derived to properly exploits the graphics processing units (GPU) architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for real hyperspectral datasets reveal significant speedup factors, up to 164 times, with regards to optimized serial implementation.

A fast parallel hyperspectral coded aperture algorithm for compressive sensing using OpenCL

In this paper, we develop a fast implementation of an hyperspectral coded aperture (HYCA) algorithm on different platforms using OpenCL, an open standard for parallel programing on heterogeneous systems, which includes a wide variety of devices, from dense multicore systems from major manufactures such as Intel or ARM to new accelerators such as graphics processing units (GPUs), field programmable gate arrays (FPGAs), the Intel Xeon Phi and other custom devices. Our proposed implementation of HYCA significantly reduces its computational cost. Our experiments have been conducted using simulated data and reveal considerable acceleration factors. This kind of implementations with the same descriptive language on different architectures are very important in order to really calibrate the possibility of using heterogeneous platforms for efficient hyperspectral imaging processing in real remote sensing missions.

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.

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.

Synthesis of optimization of [11C] Pittsburgh compound B by the captive solvent method

Mestrado em Medicina Nuclear.

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.

Monte Carlo simulation of the basic features of the GE Millennium MG single photon emission computed tomography gamma camera

Objective - To describe and validate the simulation of the basic features of GE Millennium MG gamma camera using the GATE Monte Carlo platform. Material and methods - Crystal size and thickness, parallel-hole collimation and a realistic energy acquisition window were simulated in the GATE platform. GATE results were compared to experimental data in the following imaging conditions: a point source of 99mTc at different positions during static imaging and tomographic acquisitions using two different energy windows. The accuracy between the events expected and detected by simulation was obtained with the Mann–Whitney–Wilcoxon test. Comparisons were made regarding the measurement of sensitivity and spatial resolution, static and tomographic. Simulated and experimental spatial resolutions for tomographic data were compared with the Kruskal–Wallis test to assess simulation accuracy for this parameter. Results - There was good agreement between simulated and experimental data. The number of decays expected when compared with the number of decays registered, showed small deviation (≤0.007%). The sensitivity comparisons between static acquisitions for different distances from source to collimator (1, 5, 10, 20, 30cm) with energy windows of 126–154 keV and 130–158 keV showed differences of 4.4%, 5.5%, 4.2%, 5.5%, 4.5% and 5.4%, 6.3%, 6.3%, 5.8%, 5.3%, respectively. For the tomographic acquisitions, the mean differences were 7.5% and 9.8% for the energy window 126–154 keV and 130–158 keV. Comparison of simulated and experimental spatial resolutions for tomographic data showed no statistically significant differences with 95% confidence interval. Conclusions - Adequate simulation of the system basic features using GATE Monte Carlo simulation platform was achieved and validated.