17 resultados para Automated segmentation
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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In this thesis a semi-automated cell analysis system is described through image processing. To achieve this, an image processing algorithm was studied in order to segment cells in a semi-automatic way. The main goal of this analysis is to increase the performance of cell image segmentation process, without affecting the results in a significant way. Even though, a totally manual system has the ability of producing the best results, it has the disadvantage of taking too long and being repetitive, when a large number of images need to be processed. An active contour algorithm was tested in a sequence of images taken by a microscope. This algorithm, more commonly known as snakes, allowed the user to define an initial region in which the cell was incorporated. Then, the algorithm would run several times, making the initial region contours to converge to the cell boundaries. With the final contour, it was possible to extract region properties and produce statistical data. This data allowed to say that this algorithm produces similar results to a purely manual system but at a faster rate. On the other hand, it is slower than a purely automatic way but it allows the user to adjust the contour, making it more versatile and tolerant to image variations.
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Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers
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Submitted in part fulfillment of the requirements for the degree of Master in Computer Science
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Dissertation presented to obtain the degree of Doctor of Philosophy in Electrical Engineering, speciality on Perceptional Systems, by the Universidade Nova de Lisboa, Faculty of Sciences and Technology
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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial Para obtenção do grau de Mestre em Engenharia Informática
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.
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Proceedings of the 16th Annual Conference organized by the Insurance Law Association of Serbia and German Foundation for International Legal Co-Operation (IRZ), entitled "Insurance law, governance and transparency: basics of the legal certainty" Palic Serbia, 17-19 April 2015.
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Towards a holistic perspective of CRM, this project aims to diagnose and propose a strategy and market segmentation for Siemens Healthcare. The main underlying principle is to apply a full customer-centric outlook taking own business properties into consideration while preserving Siemens Healthcare’s culture and vision. Mainly focused on market segmentation, this project goes beyond established boundaries by employing an unbiased perspective of CRM while challenging current strategy, goals, processes, tools, initiatives and KPIs. In order to promote a sustainable business excellence strategy, this project aspires to streamline CRM strategic importance and driving the company one step forward.
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A sample of 445 consumers resident in distinct Lisbon areas was analyzed through direct observations in order to discover each lifestyle’s current proportion, applying the Whitaker Lifestyle™ Method. The findings of the conducted hypothesis tests on the population proportion unveil that Neo-Traditional and Modern Whitaker lifestyles have the significantly highest proportion, while the overall presence of different lifestyles varies across neighborhoods. The research further demonstrates the validity of Whitaker observation techniques, media consumption differences among lifestyles and the importance of style and aesthetics while segmenting consumers by lifestyles. Finally, market opportunities are provided for firms operating in Lisbon.