Thermal imaging method in the evaluation of psoriasis in upper limb region

Abstract

Abstract Psoriasis is a dermatological disorder that most often causes scaling, itching and lesions on various regions of the skin. This study aims to focus on just the upper limb region affected by psoriasis and perform image acquisition using thermographic imaging. Each and every bodily disorder has a unique heat signature and respective temperature differences. Similarly, Psoriasis also has a typical heat signature that can be clearly observed on performing automated segmentation of the thermal images. The aim of this study includes automated segmentation and GLCM feature extraction in order to understand the nature of the disorder from the thermal images, and to characterize it in a more precise manner. The segmentation algorithm used for the purpose of this study is the Fuzzy C-Means algorithm. Segmentation is performed in order to clearly characterize the region of interest (ROI). The skin temperature differences in the ROI between normal and psoriasis affected hand are important to evaluate the latter. The segmented images’ features have to be extracted in order to clearly visualize the unique aspects of Psoriasis which may not be understandable upon just clinical trials. The GLCM features are extracted using the respective algorithms. The mean average temperature difference between the normal and psoriasis was found to be 2.91°C. The percentage difference between the normal and psoriasis in measurement of average temperature was found to be 9.57%. Thermographic imaging is a non-contact method of image acquisition and is being extensively used in present day for medical study. This study will help understand Psoriasis in a more elaborate and clarified manner and aims to be used as diagnostic tool in the future.