Fusion of deep learning and handcrafted techniques in dermoscopy image analysis

Abstract

A system for identifying melanoma and other skin cancer in a dermoscopy image comprises: an image analyzer having at least one processor that instantiates at least one component stored in a memory, the at least one component comprising: a segmenter configured to segment a lesion from the rest of the image, a handcrafted feature component including: a median color splitting model for separating the image into a plurality of color regions, a vessel detection model for detecting elevated vascularity, an atypical pigment network detection model for identifying a pigment network whose structure varies in size and shape, a salient point detection model for detecting salient points based on an intensity plane of the image, a color detection model for detecting at least one of a white area, a pink shade, a pink blush, and a semi-translucency, a hair detection model for characterizing detected hairs and ruler marks, an outside model that finds the above model features on non-dark-corner areas outside the segmented area, and a classifier configured to provide a first analysis result.