Neural network–based computer-aided lung cancer detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42600-021-00173-0.pdf
Reference18 articles.
1. Bhattacharjee A, Majumder S. Automated computer-aided lung cancer detection system, vol. 537. Singapore: Springer; 2019.
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3. De Man R, Wang G, Kalra MK, Otrakji A, Hsieh S, Pelc N. Upper-bound on dose reduction in CT reconstruction for nodule detection. IEEE Access. 2016;4:4247–53. https://doi.org/10.1109/ACCESS.2016.2592941.
4. Emaminejad N, et al. Fusion of quantitative image and genomic biomarkers to improve prognosis assessment of early stage lung cancer patients. IEEE Trans Biomed Eng. 2015;63(5):1034–43. https://doi.org/10.1109/TBME.2015.2477688.
5. Gorunescu F. Intelligent decision systems in medicine - a short survey on medical diagnosis and patient management. 2015 E-Health Bioeng. Conf. EHB 2015; 2016. https://doi.org/10.1109/EHB.2015.7391552.
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1. Empowering Diagnosis: Cutting-Edge Segmentation and Classification in Lung Cancer Analysis;Computers, Materials & Continua;2024
2. Automated Lung Nodule Segmentation Using Federated Learning Through CT Images;2023 8th International Conference on Robotics and Automation Engineering (ICRAE);2023-11-17
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