Melanoma detection with hystopathology image enhancement using local Hurst exponent

Malignant melanoma is nowadays one of the most frequent type of skin cancer among white-skinned populations and one of the most malignant tumors. In this work, we investigate fractal properties of color images of dermal tissue microscopic samples as a basis for detection of malignant melanoma lesions. The enhancement image process is applied to hematoxylin-eosin stained tissue samples microscopic images. A segmented image based on a color model attribute is processed with a local Hurst transformation added with edge detection algorithm. The result is used to modulate the intensity information of the original image in order to support the expert analysis essentially in low quality images. Our findings show that fractal measures such as the Hurst exponent can be used to detect regions with a high density of melanocytes nests included in dermal tissue allowing early diagnosis of malignant melanoma tumors.