An automatic classification of pulmonary nodules for lung cancer diagnosis using novel LLXcepNN classifier
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cancer Research,Oncology,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00432-022-04539-4.pdf
Reference24 articles.
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3. Cao H, Liu H, Song E, Ma G, Xiangyang Xu, Jin R, Liu T, Hung C-C (2017) Multi-branch ensemble learning architecture based on 3D CNN for false positive reduction in lung nodule detection. IEEE Access 7:67380–67391. https://doi.org/10.1109/ACCESS.2019.2906116
4. Cao H, Liu H, Song E, Ma G, Xiangyang Xu, Jin R, Liu T, Hung C-C (2020) Two stage convolutional neural network architecture for lung nodule detection. IEEE J Biomed Health Inform 24(7):1–29. https://doi.org/10.1109/jbhi.2019.2963720
5. Gunaydin O, Gunay M, Sengel O(2019) Comparison of lung cancer detection algorithms. Scientific meeting on electrical-electronics & biomedical engineering and computer science, IEEE, 24-26 April 2019, Istanbul, Turkey. https://doi.org/10.1109/EBBT.2019.8741826
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