Deep recurrent learning based qualified sequence segment analytical model (QS2AM) for infectious disease detection using CT images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Control and Optimization,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12530-023-09554-5.pdf
Reference35 articles.
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2. Angelini E, Shah A (2021) Using artificial intelligence in fungal lung disease: CPA CT imaging as an example. Mycopathologia 186(5):733–737. https://doi.org/10.1007/s11046-021-00546-0
3. Berta L et al (2021) Automatic lung segmentation in covid-19 patients: impact on quantitative computed tomography analysis. Physica Med 87:115–122. https://doi.org/10.1016/j.ejmp.2021.06.001
4. Bertolini M, Brambilla A, Dallasta S, Colombo G (2021) High-quality chest CT segmentation to assess the impact of covid-19 disease. Int J Comput Assist Radiol Surg 16(10):1737–1747. https://doi.org/10.1007/s11548-021-02466-2
5. Bisen RG, Pande NS, Rajurkar AM (2022) The role of medical imaging in COVID-19 detection and diagnosis: a review. In: 2022 International Conference for Advancement in Technology (ICONAT)
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