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 |
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頁面 | 822-827 |
頁數 | 6 |
出版狀態 | Published - 2002 |
事件 | 2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI, United States 持續時間: 2002 5月 12 → 2002 5月 17 |
Other
Other | 2002 International Joint Conference on Neural Networks (IJCNN '02) |
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國家/地區 | United States |
城市 | Honolulu, HI |
期間 | 02-05-12 → 02-05-17 |
All Science Journal Classification (ASJC) codes
- 軟體
- 人工智慧