Abstract
In this study, a malignant melanoma diagnostic system is designed using a straightforward neural network with the back-propagation learning algorithm. Eleven features are automatically extracted from skin tumor images. The correct diagnostic rate of this system is better than the average rate of 16 dermatologists who based their diagnosis with only the slide images.
Recommended Citation
Z. Zhang et al., "Neural Networks Skin Tumor Diagnostic System," Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, 2003, Institute of Electrical and Electronics Engineers (IEEE), Jan 2003.
The definitive version is available at https://doi.org/10.1109/ICNNSP.2003.1279243
Meeting Name
2003 International Conference on Neural Networks and Signal Processing, 2003
Department(s)
Electrical and Computer Engineering
Second Department
Chemistry
Keywords and Phrases
Backpropagation; Backpropagation Learning Algorithm; Feature Extraction; Malignant Melanoma Diagnostic System; Medical Image Processing; Neural Nets; Neural Networks; Skin Tumor Diagnostic System; Skin Tumor Images; Tumours
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2003 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2003
