2 resultados para initialization uncertainty

em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal


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In this paper we aim to identify and analyze a set of variables that can potentially influence the adoption of the Balanced Scorecard (BSC) in Portuguese public and private organizations. These variables are related to the environment (perception of environmental uncertainty), with human resources (support of top management) and, information and management systems (strategic map design and establishment of cause-effect relationships between indicators and perspectives of the BSC). Hypotheses were tested using data obtained from a questionnaire sent to 591 publicly-owned organizations and 549 privately-owned organizations in Portugal, with an overall response rate of 31.3%. The results allow us to conclude that the top management commitment, the development of strategy maps and the establishment of cause-effect relationships are factors that are associated with the implementation of the BSC.

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One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.