A novel deep learning approach for the detection and classification of lung nodules from CT images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15416-8.pdf
Reference28 articles.
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2. Bhatia S, Sinha Y, Goel L (2019) Lung Cancer Detection: A Deep Learning Approach. In: Lung cancer detection a deeplearning approach, 1st edn. Springer, Singapore. https://doi.org/10.1007/978-981-13-1595-4_55
3. Chlap P, Min H, Vandenberg N, Dowling J, Holloway L, Haworth A (2021) A review of medical image data augmentation techniques for deep learning applications. J Med Imaging Radiat Oncol 65(5):545–563. https://doi.org/10.1111/1754-9485.13261
4. Dongdong G, Liu G, Xue Z (2021) On the performance of lung nodule detection, segmentation and classification. Comput Med Imaging Graph 89:1–15. https://doi.org/10.1016/j.compmedimag.2021.101886
5. Fan L, Xia Z, Zhang X, Feng X (2017) Lung nodule detection based on 3D convolutionalneural networks. International conference on the Frontiers and advances in data science 23–25 Oct 2017, Xi’an, China. https://doi.org/10.1109/FADS.2017.8253184
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3. An Optimized Neural Network Model to Classify Lung Nodules from CT-Scan Images;Lecture Notes in Networks and Systems;2024
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