A shape cognitron neural network for breast cancer detection

San Kan Lee, Pau-Choo Chung, Chein I. Chang, Chien Shun Lo, Tain Lee, Giu Cheng Hsu, Chin Wen Yang

Research output: Contribution to conferencePaper

5 Citations (Scopus)

Abstract

A Neocognition-like neural network built with universal feature planes, called Shape Cognitron (S-Cognitron) is introduced to classify clustered microcalcifications (MCC's). The S-Cognitron is composed of two modules. The first module consists of (a) a shape orientation layer, to convert first-order shape orientations into numeric values, and (b) a complex layer to extract second-order shape features. Followed is a 3-D figure layer to extract the shape curvatures. It is then followed by a second module made up of a feature formation layer and a probabilistic neural network (PNN)-based classification layer, to construct "potential" high-order shape features and perform the classification. The experimental results show the promising of the system.

Original languageEnglish
Pages822-827
Number of pages6
Publication statusPublished - 2002 Jan 1
Event2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI, United States
Duration: 2002 May 122002 May 17

Other

Other2002 International Joint Conference on Neural Networks (IJCNN '02)
CountryUnited States
CityHonolulu, HI
Period02-05-1202-05-17

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All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

Cite this

Lee, S. K., Chung, P-C., Chang, C. I., Lo, C. S., Lee, T., Hsu, G. C., & Yang, C. W. (2002). A shape cognitron neural network for breast cancer detection. 822-827. Paper presented at 2002 International Joint Conference on Neural Networks (IJCNN '02), Honolulu, HI, United States.