Chapter 5 - Development of expert system for skin disease identification

Abstract

Doctors and radiologists generally follow the standard ABCD rule of dermoscopy for differentiating the malignant and benign skin lesions. The estimation of the dermoscopic score by visual inspection only, may lead to the inaccurate diagnosis of the disease at an early stage. In this chapter, the ABCD attributes have been improvised and quantified in a dermatological expert system (DermESy) for the differentiation of malignant and benign lesions. Development of DermESy, a rule-based expert system by implementing dermatologist’s knowledge with proper quantification of the dermoscopic findings is elaborated here. Using DermESy, the dermoscopic images have been categorized as malignant, benign, and suspicious lesions based on the estimated total dermoscopic score (TDS), similar to the findings of an expert. To estimate the TDS, shape, brightness, and color variations are considered to modify the “A” score. The color information extraction algorithm is introduced to extract significant color regions to quantify the “C” score. To find the appropriate “D” score of a skin lesion, dermoscopic structures segmentation algorithms have been introduced. This chapter illustrates the improvisation of the ABCD rule of dermoscopy by considering the spatial properties of dermoscopic structures for improved identification of malignant lesions. An explanatory subsystem is implemented in DermESy to assist the dermatologist with proper in-detail visualization. The dermoscopic findings and identification performances are substantiated by dermatologist to justify its acceptance as a verified second opinion to the general physicians and experts.