Refine
Year of publication
- 2020 (5) (remove)
Document type
- Master's Thesis (5) (remove)
Language
- English (5)
Has full text
- Yes (5) (remove)
Is part of the Bibliography
- No (5)
Keywords
Course of studies
Prostate segmentation is an essential part of brachytherapy treatment planning, in order to perform the procedure with required accuracy. Nowadays, segmentation of the prostate is still carried out manually during the planning steps, therefore it is a process that can be tedious, time-consuming and prone to inter-observer error. Much effort has been made in development of an computer-based algorithm that can perform prostate segmentation automatically, but only with appearance of deep learning methods, more promising algorithms emerged. So far, convolutional neural networks demonstrated excellent results in fully automatic prostate segmentation. Development of such an algorithm and training an efficient deep learning model is a challenging task, and requires a lot of optimizations. The objective of this study is development and evaluation of an algorithm for image processing based on deep learning methods that can perform fully automatic segmentation of the prostate gland in transrectal ultrasound images. Additionally, we made an overview of the development process, along with challenges and their solutions and demonstrated an algorithm implemented using Python and Tensorflow library, consisted of preprocessing, augmentation, training and validation, postprocessing and validation steps, which is able to successfully carry out fully automatic prostate segmentation with expert level of accuracy. Finally, we presented our implementation of fully convolutional neural network model and results that are encouraging to continue with model improvements and potential clinical application.
Over the past few decades, there has been an increasing amount of academic literature recognizing the significance of innovation systems. Entrepreneurship is an important component of an innovation system, contributing to the enhancement of regional as well as national innovation. The transfer of knowledge and technology between science and the economy has become particularly important to reinforce overall innovation performance. Today, universities and other institutions of higher education play a crucial role in the system of innovation and have evolved as active and highly relevant participants in the innovation system. Therefore, various supportive measures have been developed to increase the level of innovation at universities and to drive entrepreneurial activities. However, due to the ever-growing entrepreneurial support environment and the great variety of support programs,the distinction between support measures has become unclear. Consequently, the main objective of the present research work is to contribute to the overall understanding of supportive measures at German universities and other institutions of higher education.
Eight experts were interviewed to ensure the compilation of meaningful data. The research findings highlight the importance of a solid network of external experts as well as collaboration with other entrepreneurial institutions. Moreover, the research results indicated that an organizational structure with decentralized decision-making processes and a greater scope of actions enhances operational efficiency. While considering the indistinctness of different support programs and specific terms, although some significant differences were evaluated, overall, the results present a clear tendency toward a more cautious use of specialist terms, therefore substantiating the missing preciseness.
The German banking landscape is currently undergoing a paradigm shift of an unprecedented magnitude. As the financial world is changing, the future of German banks is highly uncertain. A multitude of present-day driving factors will shape the banking world of tomorrow. Therefore, this thesis aims to investigate and analyze the future of the German banking sector until 2030. The concept of scenario planning serves as underlying method for this research. Based on current factors influencing the German banking sector, the present thesis systematically develops coherent future scenarios. The generation of these scenarios is performed with the help of the scenario software INKA 4. This enables to assess a comprehensive picture of the future environment and the interactions between external influencing factors. Based on the most consistent future scenario, implications for the strategies of German banks are derived. As a result, German incumbents can question their strategic orientation and position themselves optimally for the future.
Entrepreneurship research faces a crossroads and a new approach is needed to better understand entrepreneurial behavior. Incorporating neuroscience to comprehend the entrepreneurial mindset seems promising. Nevertheless, the potential of neuroscience for entrepreneurship research is only slowly being realized. Based on an extensive literature review, this thesis examines the emerging role of neuroscience with respect to entrepreneurship. Referring to the model of the entrepreneurial process, this thesis investigates how entrepreneurs discover, exploit, and finally capture opportunities. In this context, explanations regarding trait, expertise, adaptation, and mindset of the entrepreneur are relevant for further examination. Moreover, decision-making in uncertain situations is analyzed. In this context, the dynamic interplay between the reflective and reflexive system is considered. Ultimately, this thesis provides recommendations for organizational innovation to enhance entrepreneurial
activity.
Financial technology, popularly known as Fintech, has disrupted and revolutionized the financial service sector. Today, institutions such as banks are adapting digital transformation with the help of technological devices. There is no doubt that Fintech has transformed the way we bank. Nevertheless, there has been a growing need of understanding the future of financial institution with a holistic approach. Regulatory and governmental support towards maximizing opportunity, minimizing risk, and integrating financial inclusion is needed to accelerate the economy and attain sustainable development.
The following thesis aims to study financial inclusion and how to achieve it in the Fintech industry. It comprises of four areas of influence; market, social, technology and regulatory while emphasizing on the economic development, social progress, uplifting digital finance and robust regulatory system in the globalized financial market. The research aims to close the gap among the regulatory, economic, technological and social aspects of Fintech and then develop a pathway to attain financial inclusion. In addition, the objective of the research is to provide a comprehensive strategic plan towards a prespecified future in finance. This was achieved with the help of normative scenario planning. The result was calculated using scenario planning software INKA 4. The result consisted of four distinct scenarios supporting the pathway to implement financial inclusion in Fintech sector by the year 2030.