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Christos Davatzikos | John C. Morris | Sterling C. Johnson | Ahmed Abdulkadir | Ilya M. Nasrallah | R. Nick Bryan | Mohamad Habes | Jurgen Fripp | Susan M. Resnick | Raquel E. Gur | Theodore D. Satterthwaite | Henry Völzke | Güray Erus | Jimit Doshi | Paul Maruff | Chuanjun Zhuo | Haochang Shou | Marilyn S. Albert | Yong Fan | David A. Wolk | Ruben C. Gur | Daniel H. Wolf | Dhivya Srinivasan | Hans Jörgen Grabe | Nikolaos Koutsouleris | Colin L. Masters | Vishnu M. Bashyam | M. Albert | J. Morris | H. Völzke | R. Gur | R. Gur | S. Resnick | C. Davatzikos | R. Bryan | Yong Fan | C. Masters | P. Maruff | N. Koutsouleris | D. Wolf | H. Grabe | A. Abdulkadir | M. Habes | G. Erus | J. Doshi | T. Satterthwaite | J. Fripp | D. Wolk | C. Zhuo | I. Nasrallah | H. Shou | D. Srinivasan | V. Bashyam | S. Johnson | J. Morris
[1] Aaron Carass,et al. DeepHarmony: A deep learning approach to contrast harmonization across scanner changes. , 2019, Magnetic resonance imaging.
[2] R. Gur,et al. Multisite Machine Learning Analysis Provides a Robust Structural Imaging Signature of Schizophrenia Detectable Across Diverse Patient Populations and Within Individuals , 2018, Schizophrenia bulletin.
[3] Jinhua Yu,et al. A Universal Intensity Standardization Method Based on a Many-to-One Weak-Paired Cycle Generative Adversarial Network for Magnetic Resonance Images , 2019, IEEE Transactions on Medical Imaging.
[4] Jungwoo Lee,et al. Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN , 2017, ArXiv.
[5] Daniel L. Rubin,et al. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions , 2017, Journal of Digital Imaging.
[6] P. Elliott,et al. UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.
[7] Steven G. Potkin,et al. The neuroanatomy of schizophrenia: circuitry and neurotransmitter systems , 2003, Clinical Neuroscience Research.
[8] Sidong Liu,et al. Early diagnosis of Alzheimer's disease with deep learning , 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).
[9] Zhanxing Zhu,et al. Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN , 2019, ArXiv.
[10] Nathan Srebro,et al. Exploring Generalization in Deep Learning , 2017, NIPS.
[11] N Hosten,et al. Whole-Body Magnetic Resonance Imaging of Healthy Volunteers: Pilot Study Results from the Population-Based SHIP Study , 2009, RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin.
[12] Stephen M. Smith,et al. Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.
[13] Sotirios A. Tsaftaris,et al. Medical Image Computing and Computer Assisted Intervention , 2017 .
[14] Jing Sui,et al. Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data , 2019, EBioMedicine.
[15] Bilwaj Gaonkar,et al. Multi-atlas skull-stripping. , 2013, Academic radiology.
[16] Christos Davatzikos,et al. Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan , 2019, NeuroImage.
[17] Michael Brady,et al. Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.
[18] Rama Chellappa,et al. Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models , 2018, ICLR.
[19] George J. Pappas,et al. Model-Based Robust Deep Learning , 2020, ArXiv.
[20] Christos Davatzikos,et al. MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide. , 2020, Brain : a journal of neurology.
[21] Mateusz Buda,et al. MRI image harmonization using cycle-consistent generative adversarial network , 2020, Medical Imaging.
[22] Konstantinos Kamnitsas,et al. Efficient multi‐scale 3D CNN with fully connected CRF for accurate brain lesion segmentation , 2016, Medical Image Anal..
[23] Dinggang Shen,et al. Landmark‐based deep multi‐instance learning for brain disease diagnosis , 2018, Medical Image Anal..
[24] M. Mallar Chakravarty,et al. Modeling and prediction of clinical symptom trajectories in Alzheimer’s disease using longitudinal data , 2018, PLoS Comput. Biol..
[25] Yoshua Bengio,et al. Generative Adversarial Networks , 2014, ArXiv.
[26] Peter A. Calabresi,et al. Deep Harmonization of Inconsistent MR Data for Consistent Volume Segmentation , 2018, SASHIMI@MICCAI.
[27] Olivier Salvado,et al. Addressing population aging and Alzheimer's disease through the Australian Imaging Biomarkers and Lifestyle study: Collaboration with the Alzheimer's Disease Neuroimaging Initiative , 2010, Alzheimer's & Dementia.
[28] I. Rossman,et al. Normal Human Aging: The Baltimore Longitudinal Study of Aging , 1986 .
[29] Chun-Nam Yu,et al. A Direct Approach to Robust Deep Learning Using Adversarial Networks , 2019, ICLR.
[30] Camilo Bermudez,et al. Inter-Scanner Harmonization of High Angular Resolution DW-MRI using Null Space Deep Learning , 2018, Lecture notes-monograph series.
[31] Christos Davatzikos,et al. Machine learning based imaging biomarkers in large scale population studies: A neuroimaging perspective , 2020 .
[32] Anders M. Dale,et al. Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer , 2006, NeuroImage.
[33] K. Ohtomo,et al. Effect of scanner in longitudinal studies of brain volume changes , 2011, Journal of magnetic resonance imaging : JMRI.
[34] Christos Davatzikos,et al. Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning. , 2020, Brain : a journal of neurology.
[35] H. Stefánsson,et al. Brain age prediction using deep learning uncovers associated sequence variants , 2019, Nature Communications.
[36] 拓海 杉山,et al. “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .