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Topic: Current Concepts in Wound Healing

Computer assessment of the composition

of a generic wound by image processing

Rohit Nayak , Pramod Kumar , Ramesh R. Galigekere 4
2,3
1
1 Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY 14623, USA.
2 Department of Plastic Surgery, King Abdulaziz Specialist Hospital, Sakaka 42421, Al‑Jouf, Saudi Arabia.
3 Department of Plastic Surgery and Burns, Kasturba Medical College, Manipal 576104, Karnataka, India.
4 Department of Biomedical Engineering, Manipal Institute of Technology, Manipal University, Manipal 576104, Karnataka, India.
Address for correspondence: Dr. Ramesh R. Galigekere, Department of Biomedical Engineering, Manipal Institute of Technology, Manipal
University, Manipal 576104, Karnataka, India. E‑mail: ramesh.galigekere@manipal.edu

ABSTRACT
Aim: This paper addresses the assessment of the composition of a general wound, in terms of all
identifiable categories of tissue and pigmentation in an attempt to improve accuracy in assessing and
monitoring wound health. Materials and Methods: A knowledgebase of clusters was built into the hue,
saturation and intensity (HSI) color space and then used for assessing wound composition. Based on the
observation that the clusters are fairly distinct, two different algorithms, that is, Mahalanobis distance (MD)
based and the rotated coordinate system (RCS) method, were used for classification. These methods
exploit the shape, spread, and orientation of each cluster. Results: The clusters in the HSI color space,
built from about 9,000 (calibrated) pixels from 48 images of various wound beds, showed 8 fairly
distinct regions. The inter‑cluster distances were consistent with the visual appearance. The efficacy
of the MD and RCS based methods in 120 experiments taken from a set of 15 test images (in terms of
average percent‑match) was found to be 91.55 and 93.71, respectively. Conclusion: Our investigations
established eight categories of tissue and pigmentation in wound beds. These findings help to determine
the stage of wound healing more accurately and comprehensively than typically permitted through use
of the 4‑color model reported in the literature for addressing specific wound types.

Key words:
Wound composition, color‑image processing, hue, saturation and intensity model, classification,
Mahalanobis distance, rotated coordinate system method

INTRODUCTION and limited in precision and consistency. A computerized
system for assessment and documentation of the evolution
Accurate assessment of wound health is essential in the of a wound is useful in providing a better understanding of
reduction of morbidity and mortality, which in turn reduces wounds, the healing process, and validation of treatment
the cost of health care. Factors characterizing the health of protocols, and wound care products.
a wound include its composition in terms of tissue type, Color composition is the most important factor in
pigmentation (with a one‑to‑one correspondence to distinct determining the status of a wound, and its computerized
colors), size (area, depth, and volume), shape, regularity
and texture. Traditionally, wound composition has been
assessed by visual inspection, which is subjective, tedious This is an open access article distributed under the terms of the Creative Commons
Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix,
Access this article online tweak, and build upon the work non-commercially, as long as the author is credited
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How to cite this article: Nayak R, Kumar P, Galigekere RR.
Computer assessment of the composition of a generic wound by image
DOI: processing. Plast Aesthet Res 2015;2:261-5.
10.4103/2347-9264.165444
Received: 15-12-2014; Accepted: 08-07-2015

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