Are physical measures good indicators of clinical image quality at low dose levels? A pilot study

Background - For dose reduction actions, the principle of “image quality as good as possible” to “image quality as good as needed” requires to know whether the physical measures and visual image quality relate. Visual evaluation and objective physical measures of image quality can appear to be different. If there is no noticeable effect on the visual image quality with a low dose but there is a objective physical measure impact, then the overall dose may be reduced without compromising the diagnostic image quality. Low dose imaging can be used for certain types of observations, e.g. thoracic scoliosis, control after metal implantation for osteosynthesis, reviewing pneumonia and tuberculosis. Aim of the study - To determine whether physical measures of noise predict visual (clinical) image quality at low dose levels.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

Melhoria da eficiência energética do processo de produção de molas para a indústria automóvel

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Ventilação mista em edifícios de habitação

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações

Caracterização hidráulica, hidrológica e do transporte sólido das principais linhas de água (ribeiras) do concelho de Câmara de Lobos: ilha da Madeira

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Hidráulica

A logística na cadeia de frio em Portugal: transporte de produtos perecíveis congelados

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica