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In recent years Deep Learning has brought about a breakthrough in Medical Image Segmentation.
A study of cross-validation and bootstrap for accuracy estimation and model selection
Ron Kohavi et al · 1995
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
Earlier work this paper cites.
Current methods in medical image segmentation
Dzung L Pham, Chenyang Xu, and Jerry L Prince · 2000
Earlier work this paper cites.
Robust object recognition with cortex-like mechanisms
Thomas Serre, Lior Wolf, Stanley Bileschi, Maximilian Riesenhuber, and Tomaso Poggio · 2007
Earlier work this paper cites.
Python programming language
Guido Van Rossum et al · 2007
Earlier work this paper cites.
Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology
Shivang Naik, Scott Doyle, Shannon Agner, Anant Madabhushi, Michael Feldman, and John Tomaszewski · 2008
Earlier work this paper cites.
Nuclear segmentation in microscope cell images: a hand-segmented dataset and comparison of algorithms
Luís Pedro Coelho, Aabid Shariff, and Robert F Murphy · 2009
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A comparative evaluation of interactive segmentation algorithms
Kevin McGuinness and Noel E O’connor · 2010
Earlier work this paper cites.
Deconvolutional networks
M. D. Zeiler, D. Krishnan, G. W. Taylor, and R. Fergus · 2010
Earlier work this paper cites.
An integrated micro-and macroarchitectural analysis of the drosophila brain by computer-assisted serial section electron microscopy
Albert Cardona, Stephan Saalfeld, Stephan Preibisch, Benjamin Schmid, Anchi Cheng, Jim Pulokas, Pavel Tomancak, and Volker Hartenstein · 2010
Earlier work this paper cites.
Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer · 2011
Earlier work this paper cites.
Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
Deep neural networks segment neuronal membranes in electron microscopy images
Dan Ciresan, Alessandro Giusti, Luca M Gambardella, and Jürgen Schmidhuber · 2012
Earlier work this paper cites.
Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude
Tijmen Tieleman and Geoffrey Hinton · 2012
Earlier work this paper cites.
Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun · 2013
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
The imagej ecosystem: an open platform for biomedical image analysis
Johannes Schindelin, Curtis T Rueden, Mark C Hiner, and Kevin W Eliceiri · 2015
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Benign and malignant breast tumors classification based on region growing and cnn segmentation
Rahimeh Rouhi, Mehdi Jafari, Shohreh Kasaei, and Peiman Keshavarzian · 2015
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Biomedical image segmentation using geometric deformable models and metaheuristics
Pablo Mesejo, Andrea Valsecchi, Linda Marrakchi-Kacem, Stefano Cagnoni, and Sergio Damas · 2015
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Image segmentation by generalized hierarchical fuzzy c-means algorithm
Yuhui Zheng, Byeungwoo Jeon, Danhua Xu, QM Wu, and Hui Zhang · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
The importance of skip connections in biomedical image segmentation
Michal Drozdzal, Eugene Vorontsov, Gabriel Chartrand, Samuel Kadoury, and Chris Pal · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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Image restoration using convolutional auto-encoders with symmetric skip connections
Xiao-Jiao Mao, Chunhua Shen, and Yu-Bin Yang · 2016
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Tensorflow: a system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al · 2016
Later among the works it cites.
An overview of gradient descent optimization algorithms
Sebastian Ruder · 2016
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Segnet: A deep convolutional encoder-decoder architecture for image segmentation
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Crowdsourcing the creation of image segmentation algorithms for connectomics
Ignacio Arganda-Carreras, Srinivas C Turaga, Daniel R Berger, Dan Cireşan, Alessandro Giusti, Luca M Gambardella, Jürgen Schmidhuber, Dmitry Laptev, Sarvesh Dwivedi, Joachim M Buhmann, et al · 2015
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Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians
Jorge Bernal, F Javier Sánchez, Gloria Fernández-Esparrach, Debora Gil, Cristina Rodríguez, and Fernando Vilariño · 2015
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Inception-v4, inception-resnet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi · 2017
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A survey on deep learning in medical image analysis
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen Awm Van Der Laak, Bram Van Ginneken, and Clara I Sánchez · 2017
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Skin lesion segmentation: U-nets versus clustering
Bill S Lin, Kevin Michael, Shivam Kalra, and Hamid R Tizhoosh · 2017
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Gland segmentation in colon histology images: The glas challenge contest
Korsuk Sirinukunwattana, Josien PW Pluim, Hao Chen, Xiaojuan Qi, Pheng-Ann Heng, Yun Bo Guo, Li Yang Wang, Bogdan J Matuszewski, Elia Bruni, Urko Sanchez, et al · 2017
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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
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Volumetric convnets with mixed residual connections for automated prostate segmentation from 3d mr images
Lequan Yu, Xin Yang, Hao Chen, Jing Qin, and Pheng-Ann Heng · 2017
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Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features
Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin S Kirby, John B Freymann, Keyvan Farahani, and Christos Davatzikos · 2017
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Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (isbi), hosted by the international skin imaging collaboration (isic)
Noel CF Codella, David Gutman, M Emre Celebi, Brian Helba, Michael A Marchetti, Stephen W Dusza, Aadi Kalloo, Konstantinos Liopyris, Nabin Mishra, Harald Kittler, et al · 2018
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Autosegmentation for thoracic radiation treatment planning: A grand challenge at aapm 2017
Jinzhong Yang, Harini Veeraraghavan, Samuel G Armato III, Keyvan Farahani, Justin S Kirby, Jayashree Kalpathy-Kramer, Wouter van Elmpt, Andre Dekker, Xiao Han, Xue Feng, et al · 2018
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2018
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Medical image analysis using convolutional neural networks: a review
Syed Muhammad Anwar, Muhammad Majid, Adnan Qayyum, Muhammad Awais, Majdi Alnowami, and Muhammad Khurram Khan · 2018
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Understanding convolution for semantic segmentation
Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell · 2018
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Philipp Tschandl, Cliff Rosendahl, and Harald Kittler · 2018
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