Abstract
Chronic wounds are a health condition that constitutes a threat to the public health and economy, having a detrimental effect on patient’s quality of life and high costs in treatment. Since chronic wounds do not perform a well-ordered reparative process, the anatomic and functional integrity of the damaged tissue are not restored, being of extreme importance the establishment of an appropriate treatment based on an accurate assessment of the state of the healing process. The aim of this research is to create an image processing methodology that characterizes chronic ulcers providing information about its area and tissue composition. The developed solution, which incorporates a flood fill algorithm to segment the ulcer and performs wound area calculation based on a calibration marker introduced during the image collection, was tested in diabetic foot ulcers, allows greater characterization of 97% of the 200 ulcers tested, with high correlation when compared with the clinical assessment, lower subjectivity, wound contamination probability and costs than conventional solutions.
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Acknowledgments
The authors gratefully acknowledge the partial funding of Project NORTE-01-0145-FEDER-000022 - SciTech - Science and Technology for Competitive and Sustainable Industries, cofinanced by Programa Operacional Regional do Norte (NORTE2020), through Fundo Europeu de Desenvolvimento Regional (FEDER) and the FCT - Foundation for Science and Technology under the project (PEst-OE/EME/LA0022/2013).
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Frade, R.A., Vardasca, R., Carvalho, R., Mendes, J. (2018). Automatic Classification of Ulcers Through Visual Spectrum Image. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_32
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DOI: https://doi.org/10.1007/978-3-319-68195-5_32
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