Performance analysis of various deep learning models based on Max-Min CNN for lung nodule classification on CT images

Author:

Mastouri Rekka,Khlifa Nawres,Neji Henda,Hantous-Zannad Saoussen

Publisher

Springer Science and Business Media LLC

Reference33 articles.

1. Cancer, F.: Figs: Atlanta: American Cancer Society. (2023). https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/2023-cancer-facts-figures.html. Accessed 06 July 2023

2. IASLC | International Association for the Study of Lung Cancer: IASLChttps://www.iaslc.org/. Accessed 06 July 2023

3. American Joint Committee on Cancer | SEER Training: https://training.seer.cancer.gov/staging/systems/ajcc/. Accessed 06 July 2023

4. Mastouri, R., Khlifa, N., Neji, H., Hantous-Zannad, S.: Transfer Learning Vs. Fine-Tuning in Bilinear CNN for Lung Nodules Classification on CT Scans. in Proceedings of the 3rd International Conference on Artificial Intelligence and Pattern Recognition 99–103 (2020). (2020). https://doi.org/10.1145/3430199.3430211

5. Mastouri, R., Neji, H., Hantous-Zannad, S., Khlifa, N.: A morphological operation-based approach for Sub-pleural lung nodule detection from CT images. in IEEE 4th Middle East Conference on Biomedical Engineering (MECBME) 84–89 (2018). (2018). https://doi.org/10.1109/MECBME.2018.8402411

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