Abstract
This study proposes a method for lung cancer tumor detection by first pre-processing DICOM files, then separating the lung and soft tissue areas of these files via a linear combination, and finally analyzing the CT images more clearly. The image processing method used in this study achieved a sensitivity of 97.96%, precision of 99.23% of, and F1-score of 98.56%. In addition, because of its higher performance in comparison with the reference dataset, it can be concluded that this image processing method has an effect on the learning result of the neural network.
| Original language | English |
|---|---|
| Title of host publication | ICTC 2021 - 12th International Conference on ICT Convergence |
| Subtitle of host publication | Beyond the Pandemic Era with ICT Convergence Innovation |
| Publisher | IEEE Computer Society |
| Pages | 1510-1512 |
| Number of pages | 3 |
| ISBN (Electronic) | 9781665423830 |
| DOIs | |
| State | Published - 2021 |
| Event | 12th International Conference on Information and Communication Technology Convergence, ICTC 2021 - Jeju Island, Korea, Republic of Duration: 20 Oct 2021 → 22 Oct 2021 |
Publication series
| Name | International Conference on ICT Convergence |
|---|---|
| Volume | 2021-October |
| ISSN (Print) | 2162-1233 |
| ISSN (Electronic) | 2162-1241 |
Conference
| Conference | 12th International Conference on Information and Communication Technology Convergence, ICTC 2021 |
|---|---|
| Country/Territory | Korea, Republic of |
| City | Jeju Island |
| Period | 20/10/21 → 22/10/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
Keywords
- DICOM image processing
- Deep learning
- Lung cancer detection
