Automated Pressure Ulcer Lesion Diagnosis: An Initial Study

Authors:
Dimitrios I. Kosmopoulos;Fotini L. Tzevelekou
Affiliations:
National Centre for Scientific Research “Demokritos”, Institute of Informatics and Telecommunications, Greece;Intensive Care Unit, 251 General Air Force Hospital, Greece
Venue:
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Year:
2007

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Abstract

The timely diagnosis and treatment of pressure ulcers is a critical task and constitutes a challenge in patient rehabilitation. In this chapter we present a preliminary study for automated pressure ulcer stage classification using standard image processing techniques and an SVM classifier. The deployment requirements, the internal architecture as well as the employed techniques are outlined. Furthermore, the preliminary processing results are provided to demonstrate the feasibility of automated classification of pressure ulcer regions in various grades. The methodology can be applied to segmentation--based image classification tasks, provided that colour and texture can give meaningful information.