Influência da experiência profissional e da função visual do operador no processamento semiautomático da cintigrafia de perfusão do miocárdio: variabilidade intra e interoperador na determinação dos parâmetros quantitativos

Introdução – A cintigrafia de perfusão do miocárdio (CPM) desempenha um importante papel no diagnóstico, avaliação e seguimento de pacientes com doença arterial coronária, sendo o seu processamento realizado maioritariamente de forma semiautomática. Uma vez que o desempenho dos técnicos de medicina nuclear (TMN) pode ser afetado por fatores individuais e ambientais, diferentes profissionais que processem os mesmos dados poderão obter diferentes estimativas dos parâmetros quantitativos (PQ). Objetivo – Avaliar a influência da experiência profissional e da função visual no processamento semiautomático da CPM. Analisar a variabilidade intra e interoperador na determinação dos PQ funcionais e de perfusão. Metodologia – Selecionou-se uma amostra de 20 TMN divididos em dois grupos, de acordo com a sua experiência no software Quantitative Gated SPECTTM: Grupo A (GA) – TMN ≥600h de experiência e Grupo B (GB) – TMN sem experiência. Submeteram-se os TMN a uma avaliação ortóptica e ao processamento de 21 CPM, cinco vezes, não consecutivas. Considerou-se uma visão alterada quando pelo menos um parâmetro da função visual se encontrava anormal. Para avaliar a repetibilidade e a reprodutibilidade recorreu-se à determinação dos coeficientes de variação, %. Na comparação dos PQ entre operadores, e para a análise do desempenho entre o GA e GB, aplicou-se o Teste de Friedman e de Wilcoxon, respetivamente, considerando o processamento das mesmas CPM. Para a comparação de TMN com visão normal e alterada na determinação dos PQ utilizou-se o Teste Mann-Whitney e para avaliar a influência da visão para cada PQ recorreu-se ao coeficiente de associação ETA. Diferenças estatisticamente significativas foram assumidas ao nível de significância de 5%. Resultados e Discussão – Verificou-se uma reduzida variabilidade intra (<6,59%) e inter (<5,07%) operador. O GB demonstrou ser o mais discrepante na determinação dos PQ, sendo a parede septal (PS) o único PQ que apresentou diferenças estatisticamente significativas (zw=-2,051, p=0,040), em detrimento do GA. No que se refere à influência da função visual foram detetadas diferenças estatisticamente significativas apenas na fração de ejeção do ventrículo esquerdo (FEVE) (U=11,5, p=0,012) entre TMN com visão normal e alterada, contribuindo a visão em 33,99% para a sua variação. Denotaram-se mais diferenças nos PQ obtidos em TMN que apresentam uma maior incidência de sintomatologia ocular e uma visão binocular diminuída. A FEVE demonstrou ser o parâmetro mais consistente entre operadores (1,86%). Conclusão – A CPM apresenta-se como uma técnica repetível e reprodutível, independente do operador. Verificou-se influência da experiência profissional e da função visual no processamento semiautomático da CPM, nos PQ PS e FEVE, respetivamente.

Lighting conditions and optical filters effects on visual performance of speleologists exposed to cave environments

The aim of this study is to evaluate lighting conditions and speleologists’ visual performance using optical filters when exposed to the lighting conditions of cave environments. A crosssectional study was conducted. Twenty-three speleologists were submitted to an evaluation of visual function in a clinical lab. An examination of visual acuity, contrast sensitivity, stereoacuity and flashlight illuminance levels was also performed in 16 of the 23 speleologists at two caves deprived of natural lightning. Two organic filters (450 nm and 550 nm) were used to compare visual function with and without filters. The mean age of the speleologists was 40.65 (± 10.93) years. We detected 26.1% participants with visual impairment of which refractive error (17.4%) was the major cause. In the cave environment the majority of the speleologists used a head flashlight with a mean illuminance of 451.0 ± 305.7 lux. Binocular visual acuity (BVA) was -0.05 ± 0.15 LogMAR (20/18). BVA for distance without filter was not statistically different from BVA with 550 nm or 450 nm filters (p = 0.093). Significant improved contrast sensitivity was observed with 450 nm filters for 6 cpd (p = 0.034) and 18 cpd (p = 0.026) spatial frequencies. There were no signs and symptoms of visual pathologies related to cave exposure. Illuminance levels were adequate to the majority of the activities performed. The enhancement in contrast sensitivity with filters could potentially improve tasks related with the activities performed in the cave.

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion.

Materials selection for a set of multiple parts considering manufacturing costs and weight reduction with structural isoperformance using direct multisearch optimization

Materials selection is a matter of great importance to engineering design and software tools are valuable to inform decisions in the early stages of product development. However, when a set of alternative materials is available for the different parts a product is made of, the question of what optimal material mix to choose for a group of parts is not trivial. The engineer/designer therefore goes about this in a part-by-part procedure. Optimizing each part per se can lead to a global sub-optimal solution from the product point of view. An optimization procedure to deal with products with multiple parts, each with discrete design variables, and able to determine the optimal solution assuming different objectives is therefore needed. To solve this multiobjective optimization problem, a new routine based on Direct MultiSearch (DMS) algorithm is created. Results from the Pareto front can help the designer to align his/hers materials selection for a complete set of materials with product attribute objectives, depending on the relative importance of each objective.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Exploiting the bin-class histograms for feature selection on discrete data

In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.

Identidade visual corporativa enquanto recurso estratégico na competitividade entre organizações em Portugal

Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.