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

研究成果: Paper

5 引文 (Scopus)

摘要

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.

原文English
頁面822-827
頁數6
出版狀態Published - 2002 一月 1
事件2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI, United States
持續時間: 2002 五月 122002 五月 17

Other

Other2002 International Joint Conference on Neural Networks (IJCNN '02)
國家United States
城市Honolulu, HI
期間02-05-1202-05-17

指紋

Neural networks

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

引用此文

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. 論文發表於 2002 International Joint Conference on Neural Networks (IJCNN '02), Honolulu, HI, United States.
Lee, San Kan ; Chung, Pau-Choo ; Chang, Chein I. ; Lo, Chien Shun ; Lee, Tain ; Hsu, Giu Cheng ; Yang, Chin Wen. / A shape cognitron neural network for breast cancer detection. 論文發表於 2002 International Joint Conference on Neural Networks (IJCNN '02), Honolulu, HI, United States.6 p.
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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.",
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Lee, SK, Chung, P-C, Chang, CI, Lo, CS, Lee, T, Hsu, GC & Yang, CW 2002, 'A shape cognitron neural network for breast cancer detection', 論文發表於 2002 International Joint Conference on Neural Networks (IJCNN '02), Honolulu, HI, United States, 02-05-12 - 02-05-17 頁 822-827.

A shape cognitron neural network for breast cancer detection. / Lee, San Kan; Chung, Pau-Choo; Chang, Chein I.; Lo, Chien Shun; Lee, Tain; Hsu, Giu Cheng; Yang, Chin Wen.

2002. 822-827 論文發表於 2002 International Joint Conference on Neural Networks (IJCNN '02), Honolulu, HI, United States.

研究成果: Paper

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T1 - A shape cognitron neural network for breast cancer detection

AU - Lee, San Kan

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AU - Hsu, Giu Cheng

AU - Yang, Chin Wen

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N2 - 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.

AB - 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.

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Lee SK, Chung P-C, Chang CI, Lo CS, Lee T, Hsu GC 等. A shape cognitron neural network for breast cancer detection. 2002. 論文發表於 2002 International Joint Conference on Neural Networks (IJCNN '02), Honolulu, HI, United States.