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Refer to the literature of lung nodule classification, many studies adopt Convolutional Neural Networks (CNN) to directly predict the malignancy of lung nodules with original thoracic Computed Tomography (CT) and nodule location.
“Histograms of oriented gradients for human detection,”
Navneet Dalal and Bill Triggs, · 2005
Earlier work this paper cites.
“Directional invariance of co-occurrence matrices within the liver,”
Carl Philips, Daniel Li, Daniela Raicu, and Jacob Furst, · 2008
Earlier work this paper cites.
“The lung image database consortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans,”
Samuel G Armato, Geoffrey McLennan, Luc Bidaut, Michael F McNitt-Gray, Charles R Meyer, Anthony P Reeves, Binsheng Zhao, Denise R Aberle, Claudia I Henschke, Eric A Hoffman, et al., · 2011
Earlier work this paper cites.
“Feature-based image patch approximation for lung tissue classification,”
Yang Song, Weidong Cai, Yun Zhou, and David Dagan Feng, · 2013
Earlier work this paper cites.
“Adam: A method for stochastic optimization,”
Diederik Kingma and Jimmy Ba, · 2014
Earlier work this paper cites.
“Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine,”
Hiram Madero Orozco, Osslan Osiris Vergara Villegas, Vianey Guadalupe Cruz Sánchez, Humberto de Jesús Ochoa Domínguez, and Manuel de Jesús Nandayapa Alfaro, · 2015
Earlier work this paper cites.
“Multi-scale convolutional neural networks for lung nodule classification,”
Wei Shen, Mu Zhou, Feng Yang, Caiyun Yang, and Jie Tian, · 2015
Earlier work this paper cites.
“U-net: Convolutional networks for biomedical image segmentation,”
Olaf Ronneberger, Philipp Fischer, and Thomas Brox, · 2015
Cited alongside, same era.
“Batch normalization: Accelerating deep network training by reducing internal covariate shift,”
Sergey Ioffe and Christian Szegedy, · 2015
Cited alongside, same era.
“Fast and accurate deep network learning by exponential linear units (elus),”
Djork-Arné Clevert, Thomas Unterthiner, and Sepp Hochreiter, · 2015
Cited alongside, same era.
“Cancer statistics, 2016,”
Rebecca L Siegel, Kimberly D Miller, and Ahmedin Jemal, · 2016
Cited alongside, same era.
“Automatic lung nodule classification with radiomics approach,”
Jingchen Ma, Qian Wang, Yacheng Ren, Haibo Hu, and Jun Zhao, · 2016
Cited alongside, same era.
“Lung lesion extraction using a toboggan based growing automatic segmentation approach,”
“3d u-net: learning dense volumetric segmentation from sparse annotation,”
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger, · 2016
Later among the works it cites.
“V-net: Fully convolutional neural networks for volumetric medical image segmentation,”
Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi, · 2016
Later among the works it cites.
“Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the luna16 challenge,”
Arnaud Arindra Adiyoso Setio, Alberto Traverso, Thomas De Bel, Moira SN Berens, Cas van den Bogaard, Piergiorgio Cerello, Hao Chen, Qi Dou, Maria Evelina Fantacci, Bram Geurts, et al., · 2017
Later among the works it cites.
Jia Ding, Aoxue Li, Zhiqiang Hu, and Liwei Wang, · 2017
Later among the works it cites.
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Jiangdian Song, Caiyun Yang, Li Fan, Kun Wang, Feng Yang, Shiyuan Liu, and Jie Tian, · 2016
Cited alongside, same era.
“Characterization of lung nodule malignancy using hybrid shape and appearance features,”
Mario Buty, Ziyue Xu, Mingchen Gao, Ulas Bagci, Aaron Wu, and Daniel J Mollura, · 2016
Cited alongside, same era.
Sarfaraz Hussein, Robert Gillies, Kunlin Cao, Qi Song, and Ulas Bagci, · 2017
Later among the works it cites.
“Risk stratification of lung nodules using 3d cnn-based multi-task learning,”
Sarfaraz Hussein, Kunlin Cao, Qi Song, and Ulas Bagci, · 2017
Later among the works it cites.
“Keras (2015),”
François Chollet, · 2017
Later among the works it cites.