Classification of lung cancer computed tomography images using a 3-dimensional deep convolutional neural network with multi-layer filter
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cancer Research,Oncology,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00432-023-04992-9.pdf
Reference55 articles.
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2. Bai Y, Li D, Duan Q, Chen X (2022) Analysis of high-resolution reconstruction of medical images based on deep convolutional neural networks in lung cancer diagnostics. Comput Biol Med. https://doi.org/10.1016/j.cmpb.2021.106592
3. Cai L, Long T, Huang Y (2020) Mask R-CNN-based detection and segmentation for pulmonary nodule 3D visualization diagnosis. IEEE Access 8:44400–44409. https://doi.org/10.1109/ACCESS.2020.2976432
4. Choi WJ, Choi TS (2013) Automated pulmonary nodule detection system in computed tomography images: a hierarchical block classification approach. Entropy 15(2):507–523. https://doi.org/10.3390/e15020507
5. Dai Y, Wu J, Fan Y, Wang J, Niu J, Gu F, Shen S (2022) MSEva: a musculoskeletal rehabilitation evaluation system based on EMG signals. ACM Trans Sens Netw. https://doi.org/10.1145/3522739
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