Abstract
A computer-aided diagnosis algorithm identifying breast nodule malignancy using multiple ultrasonography features and aritificial neural network classifier was developed from a database of 584 hitologically-confirmed cases containing 300 benign and 284 malignant breast nodules. The features were extracted from sonographic images through digital image processing. An artificial neural network then distinguished malignant nodules based on those features. The trained artificial neural network showed the normalized area under the receiver operating characteristic curve of 0.95.
Original language | English |
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Pages (from-to) | 1397-1400 |
Number of pages | 4 |
Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
Volume | 26 II |
State | Published - 2004 |
Event | Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States Duration: 1 Sep 2004 → 5 Sep 2004 |
Keywords
- Artificial neural network
- Computer-aided diagnosis
- Digital image processing