Attention 3D Fully Convolutional Neural Network for False Positive Reduction of Lung Nodule Detection
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-1645-0_28
Reference19 articles.
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3. Arindra, A., Setio, A., Traverso, A.: Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge. Med. Image Anal. 42, 1–13 (2017) https://doi.org/10.1016/j.media.2017.06.015
4. Arindra, A., Setio, A., Ciompi, F., et al.: Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks. IEEE 35(5), 1160–1169 (2016). https://doi.org/10.1109/TMI.2016.2536809
5. Qu, K., Chai, X., Liu, T., Zhang, Y., Leng, B., Xiong, Z.: Computer-aided diagnosis in chest radiography with deep multi-instance learning. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds.) ICONIP 2017. LNCS, vol. 10637, pp. 723–731. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70093-9_77
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