DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives

We present a new parallel algorithm for probabilistic graphical model optimization. The algorithm relies on data-parallel primitives (DPPs), which provide portable performance over hardware architecture. We evaluate results on CPUs and GPUs for an image segmentation problem. Compared to a serial baseline, we observe runtime speedups of up to 13X (CPU) and 44X (GPU). We also compare our performance to a reference, OpenMP-based algorithm, and find speedups of up to 7X (CPU).Comment: LDAV 2018, October 201

AutoCT: Automated CT registration, segmentation, and quantification

The processing and analysis of computed tomography (CT) imaging is important for both basic scientific development and clinical applications. In AutoCT, we provide a comprehensive pipeline that integrates an end-to-end automatic preprocessing, registration, segmentation, and quantitative analysis of 3D CT scans. The engineered pipeline enables atlas-based CT segmentation and quantification leveraging diffeomorphic transformations through efficient forward and inverse mappings. The extracted localized features from the deformation field allow for downstream statistical learning that may facilitate medical diagnostics. On a lightweight and portable software platform, AutoCT provides a new toolkit for the CT imaging community to underpin the deployment of artificial intelligence-driven applications

Performance Analysis of Traditional and Data-Parallel Primitive Implementations of Visualization and Analysis Kernels

Measurements of absolute runtime are useful as a summary of performance when studying parallel visualization and analysis methods on computational platforms of increasing concurrency and complexity. We can obtain even more insights by measuring and examining more detailed measures from hardware performance counters, such as the number of instructions executed by an algorithm implemented in a particular way, the amount of data moved to/from memory, memory hierarchy utilization levels via cache hit/miss ratios, and so forth. This work focuses on performance analysis on modern multi-core platforms of three different visualization and analysis kernels that are implemented in different ways: one is "traditional", using combinations of C++ and VTK, and the other uses a data-parallel approach using VTK-m. Our performance study consists of measurement and reporting of several different hardware performance counters on two different multi-core CPU platforms. The results reveal interesting performance differences between these two different approaches for implementing these kernels, results that would not be apparent using runtime as the only metric

Three-dimensional localization of nanoscale battery reactions using soft X-ray tomography.

Battery function is determined by the efficiency and reversibility of the electrochemical phase transformations at solid electrodes. The microscopic tools available to study the chemical states of matter with the required spatial resolution and chemical specificity are intrinsically limited when studying complex architectures by their reliance on two-dimensional projections of thick material. Here, we report the development of soft X-ray ptychographic tomography, which resolves chemical states in three dimensions at 11 nm spatial resolution. We study an ensemble of nano-plates of lithium iron phosphate extracted from a battery electrode at 50% state of charge. Using a set of nanoscale tomograms, we quantify the electrochemical state and resolve phase boundaries throughout the volume of individual nanoparticles. These observations reveal multiple reaction points, intra-particle heterogeneity, and size effects that highlight the importance of multi-dimensional analytical tools in providing novel insight to the design of the next generation of high-performance devices

Near-edge X-ray Refraction Fine Structure Microscopy

We demonstrate a method for obtaining increased spatial resolution and specificity in nanoscale chemical composition maps through the use of full refractive reference spectra in soft x-ray spectro-microscopy. Using soft x-rayptychography, we measure both the absorption and refraction of x-rays through pristine reference materials as a function of photon energy and use these reference spectra as the basis for decomposing spatially resolved spectra from a heterogeneous sample, thereby quantifying the composition at high resolution. While conventional instruments are limited to absorption contrast, our novel refraction based method takes advantage of the strongly energy dependent scattering cross-section and can see nearly five-fold improved spatial resolutionon resonance

Detection of thin and ramified structures in images using Markov random fields and perceptual information

Estruturas do tipo linha/curva (line-like, curve-like), alongadas e ramificadas são comumente encontradas nos ecossistemas que conhecemos. Na biomedicina e na biociências, por exemplo, diversas aplicações podem ser observadas. Justamente por este motivo, extrair este tipo de estrutura em imagens é um constante desafio em problemas de análise de imagens. Porém, diversas dificuldades estão envolvidas neste processo. Normalmente as características espectrais e espaciais destas estruturas podem ser muito complexas e variáveis. Especificamente as mais \"finas\" são muito frágeis a qualquer tipo de processamento realizado na imagem e torna-se muito fácil a perda de informações importantes. Outro problema bastante comum é a ausência de parte das estruturas, seja por motivo de pouca resolução, ou por problemas de aquisição, ou por casos de oclusão. Este trabalho tem por objetivo explorar, descrever e desenvolver técnicas de detecção/segmentação de estruturas finas e ramificadas. Diferentes métodos são utilizados de forma combinada, buscando uma melhor representação topológica e perceptual das estruturas e, assim, melhores resultados. Grafos são usados para a representação das estruturas. Esta estrutura de dados vem sendo utilizada com sucesso na literatura na resolução de diversos problemas em processamento e análise de imagens. Devido à fragilidade do tipo de estrutura explorado, além das técnicas de processamento de imagens, princípios de visão computacional são usados. Busca-se, desta forma, obter um melhor \"entendimento perceptual\" destas estruturas na imagem. Esta informação perceptual e informações contextuais das estruturas são utilizadas em um modelo de campos aleatórios de Markov, buscando o resultado final da detecção através de um processo de otimização. Finalmente, também propomos o uso combinado de diferentes modalidades de imagens simultaneamente. Um software é resultado da implementação do arcabouço desenvolvido e o mesmo é utilizado em duas aplicações para avaliar a abordagem proposta: extração de estradas em imagens de satélite e extração de raízes em imagens de perfis de solo. Resultados do uso da abordagem proposta na extração de estradas em imagens de satélite mostram um melhor desempenho em comparação com método existente na literatura. Além disso, a técnica de fusão proposta apresenta melhora significativa de acordo com os resultados apresentados. Resultados inéditos e promissores são apresentados na extração de raízes de plantas.Line- curve-like, elongated and ramified structures are commonly found inside many known ecosystems. In biomedicine and biosciences, for instance, different applications can be observed. Therefore, the process to extract this kind of structure is a constant challenge in image analysus problems. However, various difficulties are involved in this process. Their spectral and spatial characteristics are usually very complex and variable. Considering specifically the thinner ones, they are very \"fragile\" to any kind of process applied to the image, and then, it becomes easy the loss of crucial data. Another very common problem is the absence of part of the structures, either because of low image resolution and image acquisition problems or because of occlusion problems. This work aims to explore, describe and develop techniques for detection/segmentation of thin and ramified structures. Different methods are used in a combined way, aiming to reach a better topological and perceptual representation of the structures and, therefore, better results. Graphs are used to represent the structures. This data structure has been successfully used in the literature for the development of solutions for many image processing and analysis problems. Because of the fragility of the kind of structures we are dealing with, some computer vision principles are used besides usual image processing techniques. In doing so, we search for a better \"perceptual understanding\" of these structures in the image. This perceptual information along with contextual information about the structures are used in a Markov random field, searching for a final detection through an optimization process. Lastly, we propose the combined use of different image modalities simultaneously. A software is produced from the implementation of the developed framework and it is used in two application in order to evaluate the proposed approach: extraction of road networks from satellite images and extraction of plant roots from soil profile images. Results using the proposed approach for the extraction of road networks show a better performance if compared with an existent method from the literature. Besides that, the proposed fusion technique presents a meaningful improvement according to the presented results. Original and promising results are presented for the extraction of plant roots from soil profile images

Restauração de imagens em vibro-acustografia

Vibro-acoustography is an imaging modality that produces a map of the mechanical response of an object to a localized dynamic radiation force produced by an ultrasound field. This technique has been studied and used in clinical applications as to image calcification in breast tissue and arteries. This work aims to apply restoration algorithms to vibro-acoustography images. The point spread function (PSF) of the system is defined in terms of the acoustic emission of a point-target in response to a dynamic radiation stress of ultrasound. This PSF is used to form the image taking into account depth-of-field effects. The main problem found in the vibro-acoustography image formation is the high blur that this PSF causes to the acquired images, mainly in the depth direction (axial axis). To form the degraded image, digital phantoms were used, of breast for instance, simulating tissues with lesion-like inclusions. Moreover, Gaussian noise is added to the blurring model because of the characteristics of the images acquisition by the real vibro-acoustography system. Restoration filters are studied and applied to the images, and their results are compared visually and quantitatively; acceptable results are obtained. Problems found in the implementation of the restoration algorithms for this system are studied and possible solutions are discussed and applied to the final implementations. With the use of the algorithms high quality images were obtained if compared with the degraded versions, fact that justify the use of these methods in this kind of image. Moreover, the algorithms implemented in this work can be applied to imaging problems with similar characteristics.Universidade Federal de Sao CarlosA Vibro-acustografia é uma modalidade de imageamento que produz um mapa da resposta mecânica de um objeto a uma força localizada de radiação acústica dinâmica produzida por um campo de ultrassom. Esta técnica tem sido estudada e usada em aplicações clínicas como imageamento de calcificações em tecido de mamas e artérias. Este trabalho tem como objetivo a aplicação de algoritmos de restauração em imagens de vibro-acustografia. A função de espalhamento pontual (PSF) do sistema é definida em termos da emissão acústica de um alvo pontual em resposta a um stress de radiação dinâmica de ultrassom. Esta PSF é usada para formar a imagem levando em consideração efeitos de profundidade de campo. O principal problema encontrado na formação das imagens de vibro-acustografia é o alto borramento que esta PSF causa nas imagens adquiridas, principalmente em profundidade (eixo axial). Para formar a imagem degradada, foram usados phantoms digitais, de mama por exemplo, simulando tecidos com inclusões parecidas com lesões. Além disso, é adicionado ruído Gaussiano no modelo de borramento das imagens devido às características de aquisição das imagens pelo sistema real de vibro-acustografia. Filtros de restauração são estudados e aplicados às imagens, e seus resultados são comparados visualmente e quantitativamente; resultados aceitáveis são obtidos. Problemas encontrados na implementação dos algoritmos de restauração para este sistema são abordados e soluções possíveis são discutidas e aplicadas nas implementações finais. Com o uso dos algoritmos foram obtidas imagens de alta qualidade se comparadas com as versões degradadas, fato que justifica o emprego destes métodos neste tipo de imagem. Além disso, os algoritmos implementados por este trabalho poderão ser aplicados a problemas de imageamento com características similares

Introduction to Image Processing Using RLearning by Examples /

XV, 87 p. 42 illus., 17 illus. in color.online re