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Automated Lymph Node (LN) detection is an important clinical diagnostic task but very challenging due to the low contrast of surrounding structures in Computed Tomography (CT) and to their varying sizes, poses, shapes and sparsely distributed locations.
New guidelines to evaluate the response to treatment in solid tumors
Therasse, P., S. G. Arbuck, E. A. Eisenhauer, J. Wanders, R. S. Kaplan, L. Rubinstein, J. Verweij, M. Van Glabbeke, A. T. van Oosterom, M. C. Christian, et al. (2000) · 2000
Earlier work this paper cites.
A statistical 3-d pattern processing method for computer-aided detection of polyps in ct colonography
Göktürk, S. B., C. Tomasi, B. Acar, C. F. Beaulieu, D. S. Paik, R. B. Jeffrey, J. Yee, and Y. Napel (2001) · 2001
Earlier work this paper cites.
Automatic mediastinal lymph node detection in chest ct
Feuerstein, M., D. Deguchi, T. Kitasaka, S. Iwano, K. Imaizumi, Y. Hasegawa, Y. Suenaga, and K. Mori (2009) · 2009
Earlier work this paper cites.
Convolutional networks can learn to generate affinity graphs for image segmentation
Turaga, S. C., J. F. Murray, V. Jain, F. Roth, M. Helmstaedter, K. Briggman, W. Denk, and H. S. Seung (2010) · 2010
Earlier work this paper cites.
Automatic detection and segmentation of lymph nodes from ct data
Barbu, A., M. Suehling, X. Xu, D. Liu, S. K. Zhou, and D. Comaniciu (2012) · 2012
Earlier work this paper cites.
Mediastinal atlas creation from 3-d chest computed tomography images: Application to automated detection and station mapping of lymph nodes
Feuerstein, M., B. Glocker, T. Kitasaka, Y. Nakamura, S. Iwano, and K. Mori (2012) · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Krizhevsky, A., I. Sutskever, and G. E. Hinton (2012) · 2012
Cited alongside, same era.
Mitosis detection in breast cancer histology images with deep neural networks
Cireşan, D., A. Giusti, L. Gambardella, and J. Schmidhuber (2013) · 2013
Cited alongside, same era.
Lymph node detection and segmentation in chest ct data using discriminative learning and a spatial prior
Feulner, J., S. Kevin Zhou, M. Hammon, J. Hornegger, and D. Comaniciu (2013) · 2013
Cited alongside, same era.
Automatic abdominal lymph node detection method based on local intensity structure analysis from 3d x-ray CT images
Nakamura, Y., Y. Nimura, T. Kitasaka, S. Mizuno, K. Furukawa, H. Goto, M. Fujiwara, K. Misawa, M. Ito, S. Nawano, et al. (2013) · 2013
Cited alongside, same era.
Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network
Prasoon, A., K. Petersen, C. Igel, F. Lauze, E. Dam, and M. Nielsen (2013) · 2013
Cited alongside, same era.
Regularization of neural networks using dropconnect
Wan, L., M. Zeiler, S. Zhang, Y. L. Cun, and R. Fergus (2013) · 2013
Later among the works it cites.
Visualizing and understanding convolutional networks
Zeiler, M. D. and R. Fergus (2013) · 2013
Later among the works it cites.
Abdominal lymphadenopathy detection using random forest
Cherry, K. M., S. Wang, E. B. Turkbey, and R. M. Summers (2014) · 2014
Closest in time.
Mediastinal lymph node detection on thoracic CT scans using spatial prior from multi-atlas label fusion
Liu, J., J. Zhao, J. Hoffman, J. Yao, W. Zhang, E. B. Turkbey, S. Wang, C. Kim, and R. M. Summers (2014) · 2014
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2d view aggregation for lymph node detection using a shallow hierarchy of linear classifiers
Seff, A., L. Lu, H. R. Roth, K. Cherry, J. Liu, S. Wang, J. Hoffman, E. Turkbey, and R. M. Summers (2014) · 2014
Closest in time.
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