Segmentation of blood vessels from magnetic resonance angiography (MRA) or computed tomography angiography (CTA) images is a complex process that usually takes a lot of computational resources. Also, most vascular segmentation and detection algorithms do not work properly due to the wide architectural variability of the blood vessels. Thus, the construction of convincing synthetic vascular trees makes it possible to validate new segmentation methodologies. In this work, an extension to the traditional Lindenmayer system (L-system) that generates synthetic 3D blood vessels by adding stochastic rules and parameters to the grammar is proposed. Towards this aim, we implement a parser and a generator of L-systems whose grammars simulate natural features of real vessels such as the bifurcation angle, average length and diameter, as well as vascular anomalies, such as aneurysms and stenoses. The resulting expressions are then used to create synthetic vessel images that mimic MRA and CTA images. In addition, this methodology allows for vessel growth to be limited by arbitrary 3D surfaces, and the vessel intensity profile can be tailored to match real angiographic intensities.

Introduction: Intravascular optical coherence tomography (IVOCT) is an in-vivo imaging modality based on the introduction of a catheter in a blood vessel for viewing its inner wall using electromagnetic radiation. One of the most developed automatic applications for this modality is the lumen area segmentation, however on the evaluation of these methods, the slices inside bifurcation regions, or with the presence of complex atherosclerotic plaques and dissections are usually discarded. This paper describes a fully-automatic method for computing the lumen area in IVOCT images where the set of slices includes complex atherosclerotic plaques and dissections. Methods: The proposed lumen segmentation method is divided into two steps: preprocessing, including the removal of artifacts and the second step comprises a lumen detection using morphological operations. In addition, it is proposed an approach to delimit the lumen area for slices inside bifurcation region, considering only the main branch. Results: Evaluation of the automatic lumen segmentation used manual segmentations as a reference, it was performed on 1328 human IVOCT images, presenting a mean difference in lumen area and Dice metrics of 0.19 mm 2 and 97% for slices outside the bifurcation, 1.2 mm 2 and 88% in the regions with bifurcation without automatic contour correction and 0.52 mm 2 and 90% inside bifurcation region with automatic contour correction. Conclusion: This present study shows a robust lumen segmentation method for vessel cross-sections with dissections and complex plaque and bifurcation avoiding the exclusion of such regions from the dataset analysis.

No abstract

No abstract

Esse artigo descreve resultados preliminares de um estudo qualitativo conduzido com homens e mulheres empregados em uma empresa naárea de tecnologia. Foram conduzidos quatro grupos focais com dois objetivos principais: (i) identificar as influências mais relevantes que as pessoas selecionadas receberam no momento em que optaram por um curso superior naárea de tecnologia; e (ii) verificar se esses fatores diferem entre profissionais do sexo masculino e feminino. Nossas observações indicam que o processo da escolha de uma carreira difere entre os gêneros: enquanto homens buscam especialmente satisfação pessoal e financeira, mulheres demonstram uma maior preocupação a respeito da sua decisão peranteá família e sociedade.