Abstract
(Aim) In order to detect pathological brains in a more efficient way, (Method) we proposed a novel system of pathological brain detection (PBD) that combined wavelet packet Tsallis entropy (WPTE), feedforward neural network (FNN), and real-coded biogeography-based optimization (RCBBO). (Results) The experiments showed the proposed WPTE + FNN + RCBBO approach yielded an average accuracy of 99.49% over a 255-image dataset. (Conclusions) The WPTE + FNN + RCBBO performed better than 10 state-of-the-art approaches.
| Original language | English |
|---|---|
| Pages (from-to) | 275-291 |
| Number of pages | 17 |
| Journal | Fundamenta Informaticae |
| Volume | 151 |
| Issue number | 1-4 |
| DOIs | |
| Publication status | Published - 2017 |
| Externally published | Yes |
Keywords
- Feed-forward neural network
- Pathological brain detection
- Real-coded biogeography-based optimization
- Wavelet packet Tsallis entropy
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