ARTIFICIAL INTELLIGENCE FOR WOUND IMAGE UNDERSTANDING

Augustin Prodan, Mădălina Rusu, Remus Câmpean, Rodica Prodan

Abstract

This paper presents an e-learning framework for analyzing, processing and understanding wound images, to be used in teaching, learning and research activities. We intend to promote e-learning technologies in medical, pharmaceutical and health care domains. Our approach to e-learning is so called blended learning, which combines traditional face-to-face and Web-based on-line learning, with focus on principles of active learning. Using Java and XML technologies, we build models for various categories of wounds, due to various aetiologies. Based on colour and texture analysis, we identify the main barriers to wound healing, such as tissue non-viable, infection, inflammation, moisture imbalance, or edge non-advancing. This framework provides the infrastructure for preparing e-learning scenarios based on practice and real world experiences. We make experiments for wound healing simulation using various treatments and compare the results with experimental observations. Our experiments are supported by XML based databases containing knowledge extracted from previous wound healing experiences and from medical experts knowledge. Also, we rely on new paradigms of the Artificial Intelligence for creating e-learning scenarios to be used in a context of active learning, for wound image understanding. To implement the e-learning tools, we use Java technologies for dynamic processes and XML technologies for dynamic content.

References

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  5. Prodan, A., Câmpean, R., Rusu, M., Prodan, R., 2007. An e-learning framework for wound image understanding. In C. P. Constantinou et al. (Eds.), Proceedings of the CBLIS 2007 (Computer Based Learning In Science), Contemporary Perspectives on New Technologies in Science and Education, pp. 225-235, ISBN 978-9963- 671-06-9, 30 June - 6 July 2007, Crete Island.
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Paper Citation


in Harvard Style

Prodan A., Rusu M., Câmpean R. and Prodan R. (2008). ARTIFICIAL INTELLIGENCE FOR WOUND IMAGE UNDERSTANDING . In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-37-1, pages 213-218. DOI: 10.5220/0001689002130218


in Bibtex Style

@conference{iceis08,
author={Augustin Prodan and Mădălina Rusu and Remus Câmpean and Rodica Prodan},
title={ARTIFICIAL INTELLIGENCE FOR WOUND IMAGE UNDERSTANDING},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2008},
pages={213-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001689002130218},
isbn={978-989-8111-37-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - ARTIFICIAL INTELLIGENCE FOR WOUND IMAGE UNDERSTANDING
SN - 978-989-8111-37-1
AU - Prodan A.
AU - Rusu M.
AU - Câmpean R.
AU - Prodan R.
PY - 2008
SP - 213
EP - 218
DO - 10.5220/0001689002130218