Characterization of thermographic images of skin cancer lesions using digital image processing

Abstract

Skin cancer is the type of cancer with the highest incidence in the world. The alterations of temperature in the skin are organic indicators of the presence of several types of skin cancer, mainly squamous cell carcinomas and melanomas. In this work, thermographic images of lesions of this type were analyzed in order to find indicators of the presence of this neoplasm that allow the future development of a detection algorithm. The digital processing used consists of identification of areas of interest, color segmentation, quantitative discrimination according to color tonality and analysis by histograms. The results showed that lesions with skin cancer have values in the red component above 100 under the RGB color space on a scale of 0 to 255. Also, when segmenting, by the k-means algorithm, a thermography containing a melanoma, the area that contains the lesion has a higher average value in the red component with respect to the other areas. Taking these results into account, a non-invasive tool for prediagnosing skin cancer can be developed that reduces unnecessary clinical procedures and simplifies the diagnosis.

Selection of Image Texture Analysis and Color Model in the Advanced Image Processing of Thermal Images of Horses following Exercise

“…Moreover, in the RGB color model, the acquired image does not need any further transformation to display features of image texture. Therefore, the RGB color model is considered the default color model for most image applications [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 36 , 39 , 42 ], and researchers do not typically investigate other available color models. Our findings support the selection of the RGB color model as a default color model for the analysis of image texture of equine IRT images.…”

“…Digital image processing has been applied successfully in the detection of damage to composite materials [ 29 ], aerospace structures [ 30 ], and building elements [ 31 ], thus increasing the efficiency of non-destructive material testing. Similarly, increased efficiency has been reported in the detection of diabetes [ 32 ], skin cancer [ 33 ], and breast tumors [ 34 ]. Digital image analysis of thermal images is an innovative and favorable approach in many disciplines.…”

“…Fortunately, in recent times, digital image processing has been developed for more comprehensive IRT image analysis. Such image processing provides quantified, objective data considered to be more informative than conventional temperature measures in the fields of material mechanics [ 29 , 30 , 31 ] and human medicine [ 32 , 33 , 34 , 35 , 36 , 37 ]. Digital image processing has been applied successfully in the detection of damage to composite materials [ 29 ], aerospace structures [ 30 ], and building elements [ 31 ], thus increasing the efficiency of non-destructive material testing.…”

Advances in Thermal Image Analysis for the Detection of Pregnancy in Horses Using Infrared Thermography

“…DIP has been applied in the fields of material mechanics [ 22 , 23 , 24 ] and human medicine [ 25 , 26 , 27 , 28 , 29 , 30 ], and provides quantified, objective data considered to be more informative than conventional temperature measures. In materials science, DIP increased the efficiency of non-destructive materials testing, in the detection of damage to composite materials [ 22 ], aerospace structures [ 23 ], and building elements [ 24 ].…”

“…In materials science, DIP increased the efficiency of non-destructive materials testing, in the detection of damage to composite materials [ 22 ], aerospace structures [ 23 ], and building elements [ 24 ]. Moreover, in medical science, DIP increased the sensitivity and specificity of non-invasive diagnostic imaging, in the diagnosis of diabetes [ 25 ], skin cancer [ 26 ], and breast tumors [ 27 ]. However, the application of DIP to thermal images in equine medicine is only in the early stages of development [ 18 , 31 ].…”