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Classification of Benign and Malignant Lung Nodules Based on CT Raw Data
The employ of medical images combined with deep neural networks to assist in clinical diagnosis, therapeutic effect, and prognosis prediction is nowadays a hotspot. However, all the existing methods are designed based on the reconstructed medical images rather than the lossless raw data. Considering that medical images are intended for human eyes rather than the AI, we try to use raw data to predict the malignancy of pulmonary nodules and compared the predictive performance with CT. Experiments will prove the feasibility of diagnosis by CT raw data. We believe that the proposed method is promising to change the current medical diagnosis pipeline since it has the potential to free the radiologists.
Details
| Lead sponsor | Chinese Academy of Sciences |
|---|---|
| Status | COMPLETED |
| Enrolment | 626 |
| Start date | Mon Apr 15 2019 00:00:00 GMT+0000 (Coordinated Universal Time) |
| Completion | Thu Jun 30 2022 00:00:00 GMT+0000 (Coordinated Universal Time) |
Conditions
- Lung Cancer
- Image, Body
Interventions
- No interventions
Countries
China