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Classification of Benign and Malignant Lung Nodules Based on CT Raw Data

NCT04241614 COMPLETED

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 sponsorChinese Academy of Sciences
StatusCOMPLETED
Enrolment626
Start dateMon Apr 15 2019 00:00:00 GMT+0000 (Coordinated Universal Time)
CompletionThu Jun 30 2022 00:00:00 GMT+0000 (Coordinated Universal Time)

Conditions

Interventions

Countries

China