Computer-assisted analysis of epiluminescence microscopy images of pigmented skin lesions

Background: Epiluminescence microscopy (ELM) is a noninvasive clinical tool recently developed for the diagnosis of pigmented skin lesions (PSLs), wit h the aim of improving melanoma screening strategies. However, the complexi ty of the ELM grading protocol means that considerable expertise is require d for differential diagnosis. In this paper we propose a computer-based too l able to screen ELM images of PSLs in order to aid clinicians in the detec tion of lesion patterns useful for differential diagnosis. Methods: The method proposed is based on the supervised classification of p ixels of digitized ELM images, and leads to the construction of classes of pixels used for image segmentation. This process has two major phases, i.e. , a learning phase, where several hundred pixels are used in order to train and validate a classification model, and an application step, which consis ts of a massive classification of billions of pixels (i.e., the full image) by means of the rules obtained in the first phase. Results: Our results show that the proposed method is suitable for lesion-f rom-background extraction, for complete image segmentation into several typ ical diagnostic patterns, and for artifact rejection. Hence, our prototype has the potential to assist in distinguishing lesion patterns which are ass ociated with diagnostic information such as diffuse pigmentation, dark glob ules (black dots and brown globules), and the gray-blue veil. Conclusions: The system proposed in this paper can be considered as a tool to assist in PSL diagnosis. Cytometry 37:255-266, 1999. (C) 1999 Wiley-Liss , Inc.