Many people suffer from different skin diseases, which can be diverse and varied.
Most skin diseases cause disorders in the skin, such as changes in color, texture, and appearance
manifesting in spots, swelling, scaling, ulcers, etc. One of the diseases that represents a serious
health problem is skin cancer. The most dangerous skin cancer is malignant melanoma, which
can cause death if not detected early. Therefore, development of new and accurate diagnosis
methodologies to increase the chance of early detection is important. In this work, an analysis to
discriminate between malignant melanoma and three types of benign skin lesions–melanocytic
nevus, dermatofibroma, and seborrheic keratosis–is realized by calculating spectral indexes based
on the real and imaginary parts of a fractional nonlinear filter obtained by affecting the modulus of
the fractional Fourier transform by an exponent k. The fractional spectral indexes were calculated
by working with selected sub-images obtained by dividing the input image. Also, a variation
was implemented when the Hermite transform is used to calculate the fractional nonlinear filter.
Discrimination between malignant melanoma and benign skin lesions was achieved with a 99.7%
confidence level.Biomedical Optics Expresshttps://www.osapublishing.org/boe/abstract.cfm?uri=boe-10-12-604