<?xml version="1.0" encoding="UTF-8"?>
<feed xmlns="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <title>OAR@UM Collection:</title>
  <link rel="alternate" href="https://www.um.edu.mt/library/oar/handle/123456789/34208" />
  <subtitle />
  <id>https://www.um.edu.mt/library/oar/handle/123456789/34208</id>
  <updated>2026-04-21T02:13:24Z</updated>
  <dc:date>2026-04-21T02:13:24Z</dc:date>
  <entry>
    <title>Automated analysis of thermal images for peripheral vascular disease monitoring</title>
    <link rel="alternate" href="https://www.um.edu.mt/library/oar/handle/123456789/34218" />
    <author>
      <name />
    </author>
    <id>https://www.um.edu.mt/library/oar/handle/123456789/34218</id>
    <updated>2018-10-02T01:48:23Z</updated>
    <published>2017-01-01T00:00:00Z</published>
    <summary type="text">Title: Automated analysis of thermal images for peripheral vascular disease monitoring
Abstract: Diabetes is a significant health problem worldwide with its prevalence having&#xD;
been on the increase for at least the last 30 years and all estimates show that&#xD;
this trend will continue. Diabetic patients are at a higher risk for developing&#xD;
peripheral arterial disease (PAD). PAD is a disease in which plaque build up&#xD;
in the arteries restricts blood &#xD;
ow to the peripheries leading to complications&#xD;
such as ulcerations and amputations in the limbs.&#xD;
This work presents a system for the monitoring of peripheral arterial disease in&#xD;
the lower limbs of diabetic patients using thermal imaging. Thermal data was&#xD;
collected from three different population samples, which include both healthy&#xD;
and diabetic participants. The thermal data consists of images of the volar&#xD;
aspect of the hands, anterior aspect of the shins and dorsal aspect of the foot&#xD;
acquired using a pre-defined acquisition protocol. A set of algorithms were&#xD;
developed with the aim of automatically extracting temperature data from 44&#xD;
anatomical regions of interest across the three body regions. Analysis of this&#xD;
data may identify relevant patterns of interest which may be used to identify&#xD;
between different sub-groups in the thermal image database collected for this&#xD;
work.&#xD;
Results have shown that the regions of interest are extracted with a high&#xD;
accuracy from the participants in our database. The system also provides&#xD;
standardised and repeatable results, and does so in less time then a manual&#xD;
extraction process would take. This shows that a clinical tool which monitors&#xD;
PAD in diabetic patients based on thermal imaging is possible.
Description: M.SC.BIOMED.CYB.</summary>
    <dc:date>2017-01-01T00:00:00Z</dc:date>
  </entry>
</feed>

