No abstract

The main contribution of this method is the very design of the algorithm, highly innovative, which could also be used to deal with other pattern recognition problems of a similar nature. Other contributions are: 1. The good performance in discriminating between the pattern and the disturbing artefacts -which means that no prior preprocessing is required in this method- and between the pattern and other dermoscopic patterns; 2. It puts forward a new methodological approach for work of this kind, introducing the system specification as a required step prior to algorithm design and development, being this specification the basis for a required parameterisation -in the form of configurable parameters (with their value ranges) and set threshold values- of the algorithm and the subsequent conducting of the experiments.

No abstract

The hypopigmentation pattern is one of the indicators of the "Pattern Analysis" method, used by dermatologists in the diagnosis of melanoma in dermoscopy images. The proposed work presents a method for recognizing it using imaging techniques and two supervised machine learning processes. The method was tested against a database of 100 images, with 82.50% sensitivity and 80% specificity being obtained. This is the first research carried out on hypopigmentation pattern recognition to date.