Authors:
André de Souza Tarallo
;
Adilson Gonzaga
and
Marco Andrey Cipriano Frade
Affiliation:
USP University, Brazil
Keyword(s):
Leg Ulcer, Computer Vision, Artificial Neural Network.
Related
Ontology
Subjects/Areas/Topics:
Affective Computing
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Cardiovascular Technologies
;
Cloud Computing
;
Computing and Telecommunications in Cardiology
;
Devices
;
e-Health
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Human-Computer Interaction
;
Medical and Nursing Informatics
;
Physiological Computing Systems
;
Platforms and Applications
;
Practice Based Research Methods for Assistive Technology
;
Therapeutic Systems and Technologies
;
Wearable Sensors and Systems
Abstract:
Treatments of leg ulcers are generally expensive and those conducted through the direct manipulation for analysis of its evolution. The treatment efficiency is observed through the reduction of the size of ulcers in relation to the amount of tissues found in their beds, which are classified as granulated/slough. These results are obtained through analyses performed after consultation due to the time these analyses take. This work proposes a new non-invasive technique for the follow-up of treatments aimed at cutaneous ulcers. In this methodology, it was proposed that digital photos of cutaneous ulcers would be submitted to an artificial neural network (ANN), so that all surrounding the wound except for the wound itself could be extracted (skin/background), thus obtaining the ulcerated area. Computer vision techniques have been applied in order to classify the different types of tissues found in the ulcer bed, thus obtaining the corresponding granulation and slough percentages as well
as its area. The results obtained have been compared with the results obtained by Image J software. Finally, this methodology will be a useful tool for health professionals in relation to the quickness and precision that it will provide results along the consultation.
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