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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. (More)

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Paper citation in several formats:
de Souza Tarallo, A.; Gonzaga, A. and Andrey Cipriano Frade, M. (2008). SEGMENTATION AND CLASSIFICATION OF CUTANEOUS ULCERS IN DIGITAL IMAGES THROUGH ARTIFICIAL NEURAL NETWORKS. In Proceedings of the First International Conference on Health Informatics (BIOSTEC 2008) - Volume 2: HEALTHINF; ISBN 978-989-8111-16-6; ISSN 2184-4305, SciTePress, pages 59-65. DOI: 10.5220/0001037000590065

@conference{healthinf08,
author={André {de Souza Tarallo}. and Adilson Gonzaga. and Marco {Andrey Cipriano Frade}.},
title={SEGMENTATION AND CLASSIFICATION OF CUTANEOUS ULCERS IN DIGITAL IMAGES THROUGH ARTIFICIAL NEURAL NETWORKS},
booktitle={Proceedings of the First International Conference on Health Informatics (BIOSTEC 2008) - Volume 2: HEALTHINF},
year={2008},
pages={59-65},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001037000590065},
isbn={978-989-8111-16-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the First International Conference on Health Informatics (BIOSTEC 2008) - Volume 2: HEALTHINF
TI - SEGMENTATION AND CLASSIFICATION OF CUTANEOUS ULCERS IN DIGITAL IMAGES THROUGH ARTIFICIAL NEURAL NETWORKS
SN - 978-989-8111-16-6
IS - 2184-4305
AU - de Souza Tarallo, A.
AU - Gonzaga, A.
AU - Andrey Cipriano Frade, M.
PY - 2008
SP - 59
EP - 65
DO - 10.5220/0001037000590065
PB - SciTePress