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Article
Neural Network Based Edge Detection for Automated Medical Diagnosis
2011 IEEE International Conference on Information and Automation Proceedings: Shenzhen, China
  • Dingran Lu, California Polytechnic State University - San Luis Obispo
  • Xiao-Hua Yu, California Polytechnic State University - San Luis Obispo
  • Xiaomin Jin, California Polytechnic State University - San Luis Obispo
  • Bin Li, Smartbead Inc
  • Quan Chen, Health-coming Co. Ltd
  • Jianhua Zhu, Huzhou Central Hospital
Publication Date
6-6-2011
Abstract

Edge detection is an important but rather difficult task in image processing and analysis. In this research, artificial neural networks are employed for edge detection based on its adaptive learning and nonlinear mapping properties. Fuzzy sets are introduced during the training phase to improve the generalization ability of neural networks. The application of the proposed neural network approach to the edge detection of medical images for automated bladder cancer diagnosis is also investigated. Successful computer simulation results are obtained.

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Citation Information
Dingran Lu, Xiao-Hua Yu, Xiaomin Jin, Bin Li, et al.. "Neural Network Based Edge Detection for Automated Medical Diagnosis" 2011 IEEE International Conference on Information and Automation Proceedings: Shenzhen, China (2011) p. 343 - 348
Available at: http://works.bepress.com/xjin/34/