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Federated Learning for Breast Density Classification: A Real-World Implementation.

H. Roth, K. Chang, P. Singh, N. Neumark, W. Li, V. Gupta, S. Gupta, L. Qu, A. Ihsani, B. Bizzo, Y. Wen, V. Buch, M. Shah, F. Kitamura, M. Mendonça, V. Lavor, A. Harouni, C. Compas, J. Tetreault, P. Dogra, Y. Cheng, S. Erdal, R. White, B. Hashemian, T. Schultz, M. Zhang, A. McCarthy, B. Yun, E. Sharaf, K. Hoebel, J. Patel, B. Chen, S. Ko, E. Leibovitz, E. Pisano, L. Coombs, D. Xu, K. Dreyer, I. Dayan, R. Naidu, M. Flores, D. Rubin, and J. Kalpathy-Cramer. DART/DCL@MICCAI, volume 12444 of Lecture Notes in Computer Science, page 181-191. Springer, (2020)

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D. Roth

Daniel Roth

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Multi-atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT.Y. Wang, J. Yao, H. Roth, J. Burns, and R. Summers. CSI@MICCAI, volume 9402 of Lecture Notes in Computer Science, page 74-84. Springer, (2015)A Bottom-Up Approach for Pancreas Segmentation Using Cascaded Superpixels and (Deep) Image Patch Labeling.A. Farag, L. Lu, H. Roth, J. Liu, E. Turkbey, and R. Summers. IEEE Trans. Image Processing, 26 (1): 386-399 (2017)Unsupervised segmentation of 3D medical images based on clustering and deep representation learning.T. Moriya, H. Roth, S. Nakamura, H. Oda, K. Nagara, M. Oda, and K. Mori. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 10578 of SPIE Proceedings, page 1057820. SPIE, (2018)Improving Computer-aided Detection using Convolutional Neural Networks and Random View Aggregation.H. Roth, L. Lu, J. Liu, J. Yao, A. Seff, K. Cherry, L. Kim, and R. Summers. CoRR, (2015)Hierarchical 3D fully convolutional networks for multi-organ segmentation.H. Roth, H. Oda, Y. Hayashi, M. Oda, N. Shimizu, M. Fujiwara, K. Misawa, and K. Mori. CoRR, (2017)On the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks.C. Shen, H. Roth, H. Oda, M. Oda, Y. Hayashi, K. Misawa, and K. Mori. CoRR, (2018)Improving Vertebra Segmentation through Joint Vertebra-Rib Atlases.Y. Wang, J. Yao, H. Roth, J. Burns, and R. Summers. CoRR, (2016)Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images.Y. Tsehay, N. Lay, H. Roth, X. Wang, J. Kwak, B. Turkbey, P. Pinto, B. Wood, and R. Summers. Medical Imaging: Computer-Aided Diagnosis, volume 10134 of SPIE Proceedings, page 1013405. SPIE, (2017)Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.H. Shin, H. Roth, M. Gao, L. Lu, Z. Xu, I. Nogues, J. Yao, D. Mollura, and R. Summers. IEEE Trans. Med. Imaging, 35 (5): 1285-1298 (2016)Colonoscope tracking method based on shape estimation network.M. Oda, H. Roth, T. Kitasaka, K. Furukawa, R. Miyahara, Y. Hirooka, N. Navab, and K. Mori. Medical Imaging: Image-Guided Procedures, volume 10951 of SPIE Proceedings, page 109510Q. SPIE, (2019)

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Disambiguation of "Roth, Holger R."

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Federated Learning for Breast Density Classification: A Real-World Implementation.

Please choose a person to relate this publication to

D. Roth

Daniel Roth

Daniel Roth

Daniel Roth

Daniel Roth

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Roth, Holger R."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Federated Learning for Breast Density Classification: A Real-World Implementation.

Please choose a person to relate this publication to

D. Roth

Daniel Roth

Daniel Roth

Daniel Roth

Daniel Roth

Other publications of authors with the same name

Disambiguation

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Federated Learning for Breast Density Classification: A Real-World Implementation.