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Convolutional Neural Networks (CNNs) require a large amount of annotated data to learn from, which is often difficult to obtain in the medical domain.
Detection of pulmonary nodules at multirow-detector ct: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest ct
D. Wormanns; K. Ludwig; F. Beyer; W. Heindel; S. Diederich · 2005
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Pulmonary nodules on multi–detector row ct scans: performance comparison of radiologists and computer-aided detection
Geoffrey D Rubin, John K Lyo, David S Paik, Anthony J Sherbondy, Lawrence C Chow, Ann N Leung, Robert Mindelzun, Pamela K Schraedley-Desmond, Steven E Zinck, David P Naidich, et al · 2005
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The lung image database consortium (lidc) data collection process for nodule detection and annotation
M.F. McNitt-Gray; S.G. Armato; C.R. Meyer; A.P. Reeves; G. McLennan; R.C. Pais; J. Freymann; M.S. Brown; R.M. Engelmann; P.H. Bland; G.E. Laderach; C. Piker; J. Guo; Z. Towfic; D.P.Y. Qing; D.F. Yankelevitz; D.R. Aberle; E.J.R. van Beek; H. MacMahon; E.A. Kazerooni; B.Y. Croft; L.P. Clarke · 2007
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The lung image database consortium (lidc): an evaluation of radiologist variability in the identification of lung nodules on ct scans
S. G. Armato et al · 2007
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Workload of radiologists in united states in 2006-2007 and trends since 1991-1992
J.H. Sunshine M. Bhargavan; A.H. Kaye; H.P. Forman · 2009
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Samuel G Armato, Rachael Y Roberts, Masha Kocherginsky, Denise R Aberle, Ella A Kazerooni, Heber MacMahon, Edwin JR van Beek, David Yankelevitz, Geoffrey McLennan, Michael F McNitt-Gray, et al · 2009
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Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: the anode09 study
Bram Van Ginneken, Samuel G Armato, Bartjan de Hoop, Saskia van Amelsvoort-van de Vorst, Thomas Duindam, Meindert Niemeijer, Keelin Murphy, Arnold Schilham, Alessandra Retico, Maria Evelina Fantacci, et al · 2010
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Understanding the difficulty of training deep feedforward neural networks
X. Glorot; Y. Bengio · 2010
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Reduced lung-cancer mortality with low-dose computed tomographic screening
The National Lung Screening Trial Research Team · 2011
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Impact of a computer-aided detection (cad) system integrated into a picture archiving and communication system (pacs) on reader sensitivity and efficiency for the detection of lung nodules in thoracic ct exams
L. Bogoni; J.P. Ko; J. Alpert J et al · 2012
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Performance of computer-aided detection of pulmonary nodules in low-dose ct: comparison with double reading by nodule volume
Y. Zhao et al · 2012
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Computer-aided detection system for lung cancer in computed tomography scans: review and future prospects
M. Firmino; A.H. Morais; R.M. Mendoca; M.R. Dantas; H.R. Hekis; R. Valentim · 2014
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Adam: A method for stochastic optimization
D.P. Kingma; J. Ba · 2014
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Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the global burden of disease study 2015
H. Wang et al · 2016
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Lung cancer detection and early prevention, 2017
American Cancer Society · 2016
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Radiologist-initiated double reading of abdominal ct: retrospective analysis of the clinical importance of changes to radiology reports
P.M. Lauritzen et al · 2016
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A review of lung cancer screening and the role of computer-aided detection
B. Al Mohammad; P.C. Brennan; C. Mello-Thoms · 2017
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Steerable cnns
T.S. Cohen; M. Welling · 2017
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Harmonic networks: Deep translation and rotation equivariance
D. E. Worrall; S. J. Garbin; D. Turmukhambetov; G. J. Brostow · 2017
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On the generalization of equivariance and convolution in neural networks to the action of compact groups
R. Kondor; S. Trivedi · 2018
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Intertwiners between induced representations (with applications to the theory of equivariant neural networks)
T. S. Cohen; M. Geiger; M. Weiler · 2018
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Learning steerable filters for rotation equivariant CNNs
M. Weiler; F. A. Hamprecht; M. Storath · 2018
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Group equivariant convolutional networks
T.S. Cohen; M. Welling · 2016
Cited alongside, same era.
Exploiting cyclic symmetry in convolutional neural networks
S. Dieleman; J. D. Fauw; K. Kavukcuoglu · 2016
Cited alongside, same era.
A.A.A. Setio et al · 2016
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Lung cancer key statistics, 2017
American Cancer Society Cancer Statistics Center · 2017
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European position statement on lung cancer screening
M. Oudkerk et al · 2017
Cited alongside, same era.
Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning
B. van Ginneken · 2017
Cited alongside, same era.
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Roto-Translation covariant convolutional networks for medical image analysis
E.J. Bekkers; M.W. Lafarge; M. Veta; K.A.J. Eppenhof; J.P.W. Pluim · 2018
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Spherical CNNs
T.S. Cohen; M. Geiger; J. Koehler; M. Welling · 2018
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Covariant compositional networks for learning graphs
R. Kondor; H.T. Son; H. Pan; B. Anderson; S. Trivedi · 2018
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Health in the european union – facts and figures, September 2017
Eurostat · 2019
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