Segmentation of Diabetic Foot-Ulcer from Tsallis and Aquila-Optmizer Enhanced Images

The occurrence of the diabetes is gradually rising globally and it cause mild to severe illness in humankind. Diabetic Foot-Ulcer (DU) is one of the complications due to diabetes and it causes various problems if untreated. Appropriate screening procedure is necessary to identify the severity of the DU before the treatment is planned and implemented. This research aims to propose a methodology to extract the DU fragment from the preferred RGB-scale image for the examination. The various stages of this scheme involves in; (i) Image collection and resizing, (ii) pre-processing the images using Tsallis-entropy and Aquila-optimizer (TE+AO) assisted thresholding, (iii) extracting DU section using chosen segmentation procedure and (iv) Comparing the extracted region with ground-truth (GT) and computing the quality metrics. This study considered 500 test images for the study and the experimental investigation is implemented using MATLAB®. The merit of this scheme is verified using levelset, Chan-Vese and active-contour procedures and the achieved results are compared to verify the merit of the implemented scheme. The outcome of this study confirms that the proposed techniques presents a Dice-index of >95%, which confirms the significance of the developed tool.