Malignant melanoma is the deadliest form of all skin cancers. Approximately 32,000 new cases of malignant melanoma were diagnosed in 1991, with approximately 80 percent of patients expected to survive five years . Fortunately, if detected early, even malignant melanoma may be treated successfully. Thus, in recent years, there has been a rising interest in the automated detection and diagnosis of skin cancer, particularly malignant melanoma . In this paper, we present a novel neural network approach for the automated separation of melanoma from three other benign categories of tumors which exhibit melanoma-like characteristics. Our approach is based on devising new and discriminant features which are used as inputs to an artificial neural network for classification of tumor images as malignant or benign. We have obtained promising results using our method on real skin cancer images.
Erçal, Fikret; Chawla, C.; Stoecker, William V.; and Moss, Randy Hays, "Neural Network Diagnosis of Malignant Melanoma from Color Images" (1993). Computer Science Technical Reports. 26.
Intelligent Systems Center
© 1993 University of Missouri--Rolla, All rights reserved.