Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks von Sandfort, Veit, Yan, Ke, Pickhardt, Perry J., Summers, Ronald M.

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Progress in Fully Automated Abdominal CT Interpretation von Summers, Ronald M

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Deep learning in medical imaging and radiation therapy von Sahiner, Berkman, Pezeshk, Aria, Hadjiiski, Lubomir M., Wang, Xiaosong, Drukker, Karen, Cha, Kenny H., Summers, Ronald M., Giger, Maryellen L.

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Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning von Shin, Hoo-Chang, Roth, Holger R., Gao, Mingchen, Lu, Le, Xu, Ziyue, Nogues, Isabella, Yao, Jianhua, Mollura, Daniel, Summers, Ronald M.

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Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults von Jang, Samuel, Graffy, Peter M, Ziemlewicz, Timothy J, Lee, Scott J, Summers, Ronald M, Pickhardt, Perry J

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Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment von Graffy, Peter M, Sandfort, Veit, Summers, Ronald M, Pickhardt, Perry J

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Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation von Roth, Holger R., Le Lu, Jiamin Liu, Jianhua Yao, Seff, Ari, Cherry, Kevin, Kim, Lauren, Summers, Ronald M.

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Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation von Roth, Holger R., Lu, Le, Lay, Nathan, Harrison, Adam P., Farag, Amal, Sohn, Andrew, Summers, Ronald M.

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A Bottom-Up Approach for Pancreas Segmentation Using Cascaded Superpixels and (Deep) Image Patch Labeling von Farag, Amal, Le Lu, Roth, Holger R., Liu, Jiamin, Turkbey, Evrim, Summers, Ronald M.

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A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations von Roth, Holger R., Lu, Le, Seff, Ari, Cherry, Kevin M., Hoffman, Joanne, Wang, Shijun, Liu, Jiamin, Turkbey, Evrim, Summers, Ronald M.

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The future of digital health with federated learning von Rieke, Nicola, Hancox, Jonny, Li, Wenqi, Milletarì, Fausto, Roth, Holger R., Albarqouni, Shadi, Bakas, Spyridon, Galtier, Mathieu N., Landman, Bennett A., Maier-Hein, Klaus, Ourselin, Sébastien, Sheller, Micah, Summers, Ronald M., Trask, Andrew, Xu, Daguang, Baust, Maximilian, Cardoso, M. Jorge

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A Machine Learning Algorithm to Estimate Sarcopenia on Abdominal CT von Burns, Joseph E., Yao, Jianhua, Chalhoub, Didier, Chen, Joseph J., Summers, Ronald M.

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Abdominal multi-organ segmentation from CT images using conditional shape–location and unsupervised intensity priors von Okada, Toshiyuki, Linguraru, Marius George, Hori, Masatoshi, Summers, Ronald M., Tomiyama, Noriyuki, Sato, Yoshinobu

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Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study von Pickhardt, Perry J, Graffy, Peter M, Zea, Ryan, Lee, Scott J, Liu, Jiamin, Sandfort, Veit, Summers, Ronald M

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On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities von Reyes, Mauricio, Meier, Raphael, Pereira, Sérgio, Silva, Carlos A, Dahlweid, Fried-Michael, von Tengg-Kobligk, Hendrik, Summers, Ronald M, Wiest, Roland

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Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment von Graffy, Peter M, Liu, Jiamin, Pickhardt, Perry J, Burns, Joseph E, Yao, Jianhua, Summers, Ronald M

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Accuracy and agreement of PIRADSv2 for prostate cancer mpMRI: A multireader study von Greer, Matthew D., Brown, Anna M., Shih, Joanna H., Summers, Ronald M., Marko, Jamie, Law, Yan Mee, Sankineni, Sandeep, George, Arvin K., Merino, Maria J., Pinto, Peter A., Choyke, Peter L., Turkbey, Baris

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Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning von Tallam, Hima, Elton, Daniel C, Lee, Sungwon, Wakim, Paul, Pickhardt, Perry J, Summers, Ronald M

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Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort von Lee, Scott J, Liu, Jiamin, Yao, Jianhua, Kanarek, Andrew, Summers, Ronald M, Pickhardt, Perry J

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Automated abnormality classification of chest radiographs using deep convolutional neural networks von Tang, Yu-Xing, Tang, You-Bao, Peng, Yifan, Yan, Ke, Bagheri, Mohammadhadi, Redd, Bernadette A., Brandon, Catherine J., Lu, Zhiyong, Han, Mei, Xiao, Jing, Summers, Ronald M.

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