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  <title>OAR@UM Collection:</title>
  <link rel="alternate" href="https://www.um.edu.mt/library/oar/handle/123456789/107595" />
  <subtitle />
  <id>https://www.um.edu.mt/library/oar/handle/123456789/107595</id>
  <updated>2026-07-12T15:35:37Z</updated>
  <dc:date>2026-07-12T15:35:37Z</dc:date>
  <entry>
    <title>An initial SWOT study of the medical physics profession in Malta : the perspective of medical physicists</title>
    <link rel="alternate" href="https://www.um.edu.mt/library/oar/handle/123456789/107608" />
    <author>
      <name />
    </author>
    <id>https://www.um.edu.mt/library/oar/handle/123456789/107608</id>
    <updated>2023-03-23T10:42:41Z</updated>
    <published>2022-01-01T00:00:00Z</published>
    <summary type="text">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&#xD;
has not yet been a systematic situational analysis to determine how the profession is&#xD;
currently progressing. A SWOT study of the medical physics profession in Malta was&#xD;
therefore deemed necessary such that a strategic plan may be developed.&#xD;
Objectives: (a) To develop a vision statement for the profession in Malta. (b) To analyse&#xD;
the current state of the profession in Malta by establishing internal strengths and weaknesses                      &#xD;
of the profession, and external opportunities and threats with respect to the desired&#xD;
vision statement as perceived by the medical physicists themselves. (c) To develop an&#xD;
initial set of strategic objectives for the medical physics profession in Malta.&#xD;
Research Methodology: A mixed-method research approach was used in this study, the&#xD;
philosophical perspective was pragmatic, the research strategies were a qualitative survey&#xD;
of relevant documents for the vision statement and a mostly quantitative survey of the&#xD;
opinions of Maltese medical physicists to identify the SWOT themes. The data collection&#xD;
techniques were document analysis for the vision statement and a semi-structured online&#xD;
anonymous questionnaire for the SWOT themes, the data collection tool for the SWOT&#xD;
was a specially designed thematic template, the data analysis technique was SWOT&#xD;
analysis with the use of Microsoft Excel for numerical data.&#xD;
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&#xD;
statement were identified.&#xD;
Conclusions and Recommendations: The medical physics profession in Malta has&#xD;
many strengths and opportunities. However, there are also some weaknesses and threats.&#xD;
Strategic objectives for the profession were proposed. It is suggested that further research&#xD;
be conducted to clarify the SWOTs further by including in-depth interviews with both&#xD;
medical physicists and other stakeholders.
Description: M.Sc. Med.Phy.(Melit.)</summary>
    <dc:date>2022-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Automatic segmentation of healthy liver in abdominal computed tomography scans</title>
    <link rel="alternate" href="https://www.um.edu.mt/library/oar/handle/123456789/107607" />
    <author>
      <name />
    </author>
    <id>https://www.um.edu.mt/library/oar/handle/123456789/107607</id>
    <updated>2023-03-23T10:41:07Z</updated>
    <published>2022-01-01T00:00:00Z</published>
    <summary type="text">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&#xD;
and monitoring. At the date of writing this work, segmentation is primarily carried out&#xD;
manually by medical professionals, which adds a substantial workload.&#xD;
Convolutional Encoder-Decoders (CEDs) currently dominate the medical image automatic segmentation field and many have produced satisfactory results, given the limited&#xD;
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&#xD;
is an architecture based on VGG16, UNet and the Cascade Framework. The Combined Healthy Abdominal Organ Segmentation (CHAOS) Challenge database and its&#xD;
Task 2 framework are used to replicate and verify the state-of-the-art implementation.&#xD;
A modification of the architecture of v16pUNet1.1C was carried out with the purpose&#xD;
of increasing the performance. Modifications were also performed on the learning rate,&#xD;
context connections and the cascade framework, however, none seemed to lead to an&#xD;
increase in mean score performance, although they did narrow the interquartile range,&#xD;
which is a success in its own merit. The modified model, called v16pUNet1.1D, managed&#xD;
to achieve a mean score of 85.92, just 0.06 points shy from first place in Task 2 of the&#xD;
CHAOS Challenge.
Description: M.Sc. Med.Phy.(Melit.)</summary>
    <dc:date>2022-01-01T00:00:00Z</dc:date>
  </entry>
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