Lung nodule malignancy classification in chest computed tomography images using transfer learning and convolutional neural networks

Author:

da Nóbrega Raul Victor M.,Rebouças Filho Pedro P.ORCID,Rodrigues Murillo B.,da Silva Suane P. P.,Dourado Júnior Carlos M. J. M.,de Albuquerque Victor Hugo C.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference54 articles.

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2. de Albuquerque VHC, Damaševičius R, Garcia NM, Pinheiro PR, Filho PPR (2017) Brain computer interface systems for neurorobotics: methods and applications. BioMed Res Int 2017:1–2. https://doi.org/10.1155/2017/2505493

3. Armato SG, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR, Reeves AP, Zhao B, Aberle DR, Henschke CI, Hoffman EA, Kazerooni EA, MacMahon H, van Beek EJR, Yankelevitz D, Biancardi AM, Bland PH, Brown MS, Engelmann RM, Laderach GE, Max D, Pais RC, Qing DPY, Roberts RY, Smith AR, Starkey A, Batra P, Caligiuri P, Farooqi A, Gladish GW, Jude CM, Munden RF, Petkovska I, Quint LE, Schwartz LH, Sundaram B, Dodd LE, Fenimore C, Gur D, Petrick N, Freymann J, Kirby J, Hughes B, Casteele AV, Gupte S, Sallam M, Heath MD, Kuhn MH, Dharaiya E, Burns R, Fryd DS, Salganicoff M, Anand V, Shreter U, Vastagh S, Croft BY, Clarke LP (2011) The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys 38(2):915–931. https://doi.org/10.1118/1.3528204

4. Chollet F (2017) Xception: Deep learning with depthwise separable convolutions. In: 2017 IEEE Conference on computer vision and pattern recognition (CVPR). IEEE. https://doi.org/10.1109/cvpr.2017.195

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