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Title: Improving the precision of leg ulcer area measurement with active contour models
Author: Jones, Timothy David
ISNI:       0000 0001 3592 9600
Awarding Body: University of Glamorgan
Current Institution: University of South Wales
Date of Award: 1999
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A leg ulcer is a chronic wound of the skin that, at best, takes many months to fully heal and causes great distress to the patient. Treating leg ulcers places a large financial burden upon the National Health Service in the United Kingdom, estimated to be in excess of £300M annually. Measurement of the size of leg ulcers is a guide to assessing the progress of wound healing, and the use of non-invasive measurement techniques avoids damaging or infecting the wound. The area of a leg ulcer is currently measured by presenting a human observer with a captured video image of a wound, who then uses a mouse or pointing device to delineate the wounded region. Typically, the standard deviation of area measurements taken this way is approximately 5% of the wound area. In addition, different observers can show a bias difference in their area measurements from 3% to 25% of the wound area. It is proposed to reduce the incidence of such errors by using an active contour model to improve the delineation. Four different models are developed by adapting and applying several contributions made to the active contour model paradigm. Novel features include an external force that acts normally, but not tangentially, to the boundary, a new external energy term that promotes homogeneity of the gray level at the edge of the wound and the application of the minimax principle for setting the parameters of an active contour model with piecewise b-spline curves. The algorithms provide the physician with a new and practical tool for producing area measurements with improved precision and are semi-automatic, requiring only a manual delineation to start the algorithm. In most cases, measurement precision is improved by application of the algorithms. Many wounds give rise to measurable bias differences between average manual area measurements and the corresponding algorithmic area measurements, typically averaging 3% to 4% of wound area. With some wounds the bias magnitude can exceed 10% as a result of the contour partly deviating from the true edge of the wound and following a false edge.
Supervisor: Plassmann, Peter Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Wound measurement; Photogrammetry