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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.8 P.598-606

10.1631/jzus.C0910552


Studying pressure sores through illuminant invariant assessment of digital color images


Author(s):  Sahar Moghimi, Mohammad Hossein Miran Baygi, Giti Torkaman, Ehsanollah Kabir, Ali Mahloojifar, Narges Armanfard

Affiliation(s):  Department of Electrical Engineering, Tarbiat Modares University, P.O. Box 14115-111, Tehran, Iran, Department of Physical Therapy, Tarbiat Modares University, P.O. Box 14115-111, Tehran, Iran

Corresponding email(s):   moghimi@modares.ac.ir, miranbmh@modares.ac.ir

Key Words:  Local binary pattern (LBP), Automatic assessment, Neural networks, Color based texture model, Pressure sores, Digital color images


Sahar Moghimi, Mohammad Hossein Miran Baygi, Giti Torkaman, Ehsanollah Kabir, Ali Mahloojifar, Narges Armanfard. Studying pressure sores through illuminant invariant assessment of digital color images[J]. Journal of Zhejiang University Science C, 2010, 11(8): 598-606.

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author="Sahar Moghimi, Mohammad Hossein Miran Baygi, Giti Torkaman, Ehsanollah Kabir, Ali Mahloojifar, Narges Armanfard",
journal="Journal of Zhejiang University Science C",
volume="11",
number="8",
pages="598-606",
year="2010",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C0910552"
}

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%T Studying pressure sores through illuminant invariant assessment of digital color images
%A Sahar Moghimi
%A Mohammad Hossein Miran Baygi
%A Giti Torkaman
%A Ehsanollah Kabir
%A Ali Mahloojifar
%A Narges Armanfard
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910552

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A1 - Sahar Moghimi
A1 - Mohammad Hossein Miran Baygi
A1 - Giti Torkaman
A1 - Ehsanollah Kabir
A1 - Ali Mahloojifar
A1 - Narges Armanfard
J0 - Journal of Zhejiang University Science C
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%@ 1869-1951
Y1 - 2010
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C0910552


Abstract: 
Methods for pressure sore monitoring remain both a clinical and research challenge. Improved methodologies could assist physicians in developing prompt and effective pressure sore interventions. In this paper a technique is introduced for the assessment of pressure sores in guinea pigs, using captured color images. Sores were artificially induced, utilizing a system particularly developed for this purpose. Digital images were obtained from the suspicious region in days 3 and 7 post-pressure sore generation. Different segments of the color images were divided and labeled into three classes, based on their severity status. For quantitative analysis, a color based texture model, which is invariant against monotonic changes in illumination, is proposed. The texture model has been developed based on the local binary pattern operator. Tissue segments were classified, using the texture model and its features as inputs to a combination of neural networks. Our method is capable of discriminating tissue segments in different stages of pressure sore generation, and therefore can be a feasible tool for the early assessment of pressure sores.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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