Abstract
Hyperspectral imaging has become an emerging imaging modality for medical applications. In this work, we propose to combine both the spectral and structural information in the hyperspectral data cube for tumor detection in tongue tissue. A dual stream network is designed, with a spectral and a structural branch. Hyperspectral data (480 to 920 nm) is collected from 7 patients with tongue squamous cell carcinoma. Histopathological analysis provided ground truth labels. The proposed dual stream model outperforms the pure spectral and structural approaches with areas under the ROC-curve of 0.90, 0.87 and 0.85, respectively.
Original language | English |
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Title of host publication | ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging |
Place of Publication | Piscataway |
Publisher | IEEE Computer Society |
Pages | 1256-1259 |
Number of pages | 4 |
ISBN (Electronic) | 9781538636411 |
DOIs | |
Publication status | Published - 1 Apr 2019 |
Event | 16th IEEE International Symposium on Biomedical Imaging (ISBI 2019) - Venice, Italy Duration: 8 Apr 2019 → 11 Apr 2019 Conference number: 16 |
Conference
Conference | 16th IEEE International Symposium on Biomedical Imaging (ISBI 2019) |
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Abbreviated title | ISBI 2019 |
Country/Territory | Italy |
City | Venice |
Period | 8/04/19 → 11/04/19 |
Keywords
- Hyperspectral imaging
- Machine learning
- Neural networks
- Tongue tumor