https://www.um.edu.mt/library/oar/handle/123456789/107595 Fri, 17 Apr 2026 05:24:53 GMT 2026-04-17T05:24:53Z https://www.um.edu.mt/library/oar/handle/123456789/107608 Title: An initial SWOT study of the medical physics profession in Malta : the perspective of medical physicists Abstract: Background: In Malta, medical physics is a relatively new profession and thus far, there has not yet been a systematic situational analysis to determine how the profession is currently progressing. A SWOT study of the medical physics profession in Malta was therefore deemed necessary such that a strategic plan may be developed. Objectives: (a) To develop a vision statement for the profession in Malta. (b) To analyse the current state of the profession in Malta by establishing internal strengths and weaknesses of the profession, and external opportunities and threats with respect to the desired vision statement as perceived by the medical physicists themselves. (c) To develop an initial set of strategic objectives for the medical physics profession in Malta. Research Methodology: A mixed-method research approach was used in this study, the philosophical perspective was pragmatic, the research strategies were a qualitative survey of relevant documents for the vision statement and a mostly quantitative survey of the opinions of Maltese medical physicists to identify the SWOT themes. The data collection techniques were document analysis for the vision statement and a semi-structured online anonymous questionnaire for the SWOT themes, the data collection tool for the SWOT was a specially designed thematic template, the data analysis technique was SWOT analysis with the use of Microsoft Excel for numerical data. Results: A vision statement was proposed and the SWOTs of the medical physics profession in Malta as perceived by the local medical physicists with respect to the vision statement were identified. Conclusions and Recommendations: The medical physics profession in Malta has many strengths and opportunities. However, there are also some weaknesses and threats. Strategic objectives for the profession were proposed. It is suggested that further research be conducted to clarify the SWOTs further by including in-depth interviews with both medical physicists and other stakeholders. Description: M.Sc. Med.Phy.(Melit.) Sat, 01 Jan 2022 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/107608 2022-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/107607 Title: Automatic segmentation of healthy liver in abdominal computed tomography scans Abstract: Segmentation is the process of delineating regions of interest and this process is applied to medical scans to help with diagnosis of diseases as well as treatment planning and monitoring. At the date of writing this work, segmentation is primarily carried out manually by medical professionals, which adds a substantial workload. Convolutional Encoder-Decoders (CEDs) currently dominate the medical image automatic segmentation field and many have produced satisfactory results, given the limited availability of training data. This work explores literature of some of these implementations and goes into detail about a state-of-the-art model called v16pUNet1.1C, which is an architecture based on VGG16, UNet and the Cascade Framework. The Combined Healthy Abdominal Organ Segmentation (CHAOS) Challenge database and its Task 2 framework are used to replicate and verify the state-of-the-art implementation. A modification of the architecture of v16pUNet1.1C was carried out with the purpose of increasing the performance. Modifications were also performed on the learning rate, context connections and the cascade framework, however, none seemed to lead to an increase in mean score performance, although they did narrow the interquartile range, which is a success in its own merit. The modified model, called v16pUNet1.1D, managed to achieve a mean score of 85.92, just 0.06 points shy from first place in Task 2 of the CHAOS Challenge. Description: M.Sc. Med.Phy.(Melit.) Sat, 01 Jan 2022 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/107607 2022-01-01T00:00:00Z