The implementation of in vivo imaging technologies, such as digital photography, dermoscopy and confocal scanning laser reflectance microscopy (CSLM) in dermatology has led to recent improvements in recognizing skin lesions. Specifically, in the case of skin cancer, a key issue is that the rate of cancerous tissue growth and changes in its spatial extent with time are linked to the energy released locally by these uncontrolled metabolic processes. We believe that with a properly designed infrared (IR) imaging and measurement system combined with thermal analysis, one can characterize healthy and diseased tissue. This paper augments our previous work, in which we introduced a computational model to estimate the location and size of lesions using IR imaging data. In this paper, we focus on calibrating the IR camera and correcting its inherent artifacts. Calibration and corrections are first performed on a blackbody object and then on human skin images in order to acquire accurate surface temperature distributions. As future work, in addition to these correction steps, several other steps, such as accounting for emissivity variations will be developed for clinical studies. In addition to IR imaging, images acquired by in vivo confocal scanning laser microscopy are used to examine the structure of the human skin for different skin types. Our aim is to generate additional data necessary for the IR imaging model by further analyzing the 3D structure of healthy tissue and the lesion. Specifically, in clinical studies, confocal images will be used to describe thermal associations with skin lesion and its blood supply in order to refine our transient thermal model of skin tissue.

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