Diagnosing Malignant Melanoma using a Neural Network
In recent years, there has been a rising interest in the early detection of skin cancer, particularly malignant melanoma, via automated screening and diagnosis process. In this paper, we present a novel neural network approach for the automated distinction 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.
F. Erçal et al., "Diagnosing Malignant Melanoma using a Neural Network," Intelligent Engineering Systems Through Artificial Neural Networks, vol. 2, pp. 553-558, American Society of Mechanical Engineers (ASME), Nov 1992.
Artificial Neural Networks in Engineering (1992: Nov. 15-18, St. Louis, MO)
Electrical and Computer Engineering
Keywords and Phrases
Diagnosis; Image Analysis; Medical Imaging; Oncology; Tumor Image Diagnosis; Neural Networks
International Standard Book Number (ISBN)
Article - Conference proceedings
© 1992 American Society of Mechanical Engineers (ASME), All rights reserved.
01 Nov 1992