Nodule2vec: A 3D Deep Learning System for Pulmonary Nodule Retrieval Using Semantic Representation
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-59725-2_58
Reference18 articles.
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2. Armato III, S.G., et al.: Data from LIDC-IDRI (2015). https://doi.org/10.7937/K9/TCIA.2015.LO9QL9SX. https://wiki.cancerimagingarchive.net/x/rgAe
3. Dhara, A.K., Mukhopadhyay, S., Dutta, A., Garg, M., Khandelwal, N.: Content-based image retrieval system for pulmonary nodules: assisting radiologists in self-learning and diagnosis of lung cancer. J. Digit. Imaging 30(1), 63–77 (2016). https://doi.org/10.1007/s10278-016-9904-y
4. Hancock, M.C., Magnan, J.F.: Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the lung image database consortium dataset with two statistical learning methods. J. Med. Imaging 3(4), 044504 (2016). https://doi.org/10.1117/1.jmi.3.4.044504
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