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Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images
Computer aided detection (CAD) systems can assist radiologists by offering a second opinion on early diagnosis of lung cancer. Classification and feature representation play critical roles in false-positive reduction (FPR) in lung nodule CAD. We design a deep convolutional neural networks method for...
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| Pubblicato in: | Comput Math Methods Med |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Hindawi Publishing Corporation
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5192289/ https://ncbi.nlm.nih.gov/pubmed/28070212 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2016/6215085 |
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