Schaefer, G., Tait, R., Merla, A. and Zhu, Shao Ying (2017) Automated Overlay of Infrared and Visual Medical Images using Skin Detection and Image Registration. International Journal of Computational Vision and Biomechanics, 3 (1). pp. 81-87.

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Abstract

Thermal infrared imaging is used to capture the temperature distribution of the human skin and employed in various medical applications. Often visual images are taken in conjunction with thermograms. Clinicians are interested to cross-reference the infrared and visual images of a patient, either to see which part of the anatomy is affected by a certain disease or to judge the efficacy of treatment. In this paper, we show that image registration techniques can be used effectively to generate such an overlay of visual and thermal infrared images to provide a useful visualisation. Following a skin detection step, which segments areas corresponding to the patient in the visual image, registration techniques, either intensity- or landmarkbased, are employed to accurately align the two images. The proposed approach is shown to be effective for a variety of applications, ranging from clinical studies such as monitoring the evolution of lesions in dermatology (psoriasis, dermatitis) or in immunology (scleroderma, lupus), to the most innovative applications of functional infrared imaging, like emotion recognition through a combination of infrared imaging-based computation of autonomic responses and facial expression recognition.

Item Type:	Article
Status:	Published
School/Department:	School of Science, Technology and Health
URI:	https://ray.yorksj.ac.uk/id/eprint/9926

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