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1
Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan
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Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan

Pomponio, Raymond ; Erus, Guray ; Habes, Mohamad ; Doshi, Jimit ; Srinivasan, Dhivya ; Mamourian, Elizabeth ; Bashyam, Vishnu ; Nasrallah, Ilya M. ; Satterthwaite, Theodore D. ; Fan, Yong ; Launer, Lenore J. ; Masters, Colin L. ; Maruff, Paul ; Zhuo, Chuanjun ; Völzke, Henry ; Johnson, Sterling C. ; Fripp, Jurgen ; Koutsouleris, Nikolaos ; Wolf, Daniel H. ; Gur, Raquel ; Gur, Ruben ; Morris, John ; Albert, Marilyn S. ; Grabe, Hans J. ; Resnick, Susan M. ; Bryan, R. Nick ; Wolk, David A. ; Shinohara, Russell T. ; Shou, Haochang ; Davatzikos, Christos

NeuroImage (Orlando, Fla.), 2020-03, Vol.208, p.116450-116450, Article 116450 [Periódico revisado por pares]

United States: Elsevier Inc

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BEaST: Brain extraction based on nonlocal segmentation technique
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BEaST: Brain extraction based on nonlocal segmentation technique

Eskildsen, Simon F. ; Coupé, Pierrick ; Fonov, Vladimir ; Manjón, José V. ; Leung, Kelvin K. ; Guizard, Nicolas ; Wassef, Shafik N. ; Østergaard, Lasse Riis ; Collins, D. Louis

NeuroImage (Orlando, Fla.), 2012-02, Vol.59 (3), p.2362-2373 [Periódico revisado por pares]

United States: Elsevier Inc

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3
Assessment of the generalization of learned image reconstruction and the potential for transfer learning
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Assessment of the generalization of learned image reconstruction and the potential for transfer learning

Knoll, Florian ; Hammernik, Kerstin ; Kobler, Erich ; Pock, Thomas ; Recht, Michael P ; Sodickson, Daniel K

Magnetic resonance in medicine, 2019-01, Vol.81 (1), p.116-128 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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4
Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis
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Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Grandjean, Joanes ; Canella, Carola ; Anckaerts, Cynthia ; Ayrancı, Gülebru ; Bougacha, Salma ; Bienert, Thomas ; Buehlmann, David ; Coletta, Ludovico ; Gallino, Daniel ; Gass, Natalia ; Garin, Clément M. ; Nadkarni, Nachiket Abhay ; Hübner, Neele S. ; Karatas, Meltem ; Komaki, Yuji ; Kreitz, Silke ; Mandino, Francesca ; Mechling, Anna E. ; Sato, Chika ; Sauer, Katja ; Shah, Disha ; Strobelt, Sandra ; Takata, Norio ; Wank, Isabel ; Wu, Tong ; Yahata, Noriaki ; Yeow, Ling Yun ; Yee, Yohan ; Aoki, Ichio ; Chakravarty, M. Mallar ; Chang, Wei-Tang ; Dhenain, Marc ; von Elverfeldt, Dominik ; Harsan, Laura-Adela ; Hess, Andreas ; Jiang, Tianzi ; Keliris, Georgios A. ; Lerch, Jason P. ; Meyer-Lindenberg, Andreas ; Okano, Hideyuki ; Rudin, Markus ; Sartorius, Alexander ; Van der Linden, Annemie ; Verhoye, Marleen ; Weber-Fahr, Wolfgang ; Wenderoth, Nicole ; Zerbi, Valerio ; Gozzi, Alessandro

NeuroImage (Orlando, Fla.), 2020-01, Vol.205, p.116278-116278, Article 116278 [Periódico revisado por pares]

United States: Elsevier Inc

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5
Breast parenchymal patterns in processed versus raw digital mammograms: A large population study toward assessing differences in quantitative measures across image representations
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Breast parenchymal patterns in processed versus raw digital mammograms: A large population study toward assessing differences in quantitative measures across image representations

Gastounioti, Aimilia ; Oustimov, Andrew ; Keller, Brad M. ; Pantalone, Lauren ; Hsieh, Meng-Kang ; Conant, Emily F. ; Kontos, Despina

Medical physics (Lancaster), 2016-11, Vol.43 (11), p.5862-5877 [Periódico revisado por pares]

United States: American Association of Physicists in Medicine

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6
Sparse Representation With Kernels
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Sparse Representation With Kernels

Shenghua Gao ; Tsang, I. W. ; Liang-Tien Chia

IEEE transactions on image processing, 2013-02, Vol.22 (2), p.423-434 [Periódico revisado por pares]

New York, NY: IEEE

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7
Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation
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Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

Keller, Brad M. ; Nathan, Diane L. ; Wang, Yan ; Zheng, Yuanjie ; Gee, James C. ; Conant, Emily F. ; Kontos, Despina

Medical physics (Lancaster), 2012-08, Vol.39 (8), p.4903-4917 [Periódico revisado por pares]

United States: American Association of Physicists in Medicine

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8
A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients
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A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients

Ladefoged, Claes N. ; Law, Ian ; Anazodo, Udunna ; St. Lawrence, Keith ; Izquierdo-Garcia, David ; Catana, Ciprian ; Burgos, Ninon ; Cardoso, M. Jorge ; Ourselin, Sebastien ; Hutton, Brian ; Mérida, Inés ; Costes, Nicolas ; Hammers, Alexander ; Benoit, Didier ; Holm, Søren ; Juttukonda, Meher ; An, Hongyu ; Cabello, Jorge ; Lukas, Mathias ; Nekolla, Stephan ; Ziegler, Sibylle ; Fenchel, Matthias ; Jakoby, Bjoern ; Casey, Michael E. ; Benzinger, Tammie ; Højgaard, Liselotte ; Hansen, Adam E. ; Andersen, Flemming L.

NeuroImage (Orlando, Fla.), 2017-02, Vol.147, p.346-359 [Periódico revisado por pares]

United States: Elsevier Inc

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9
Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging
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Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging

Hunter, Chad R. R. N. ; Klein, Ran ; Beanlands, Rob S. ; deKemp, Robert A.

Medical physics (Lancaster), 2016-04, Vol.43 (4), p.1829-1840 [Periódico revisado por pares]

United States: American Association of Physicists in Medicine

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10
Generation of Structural MR Images from Amyloid PET: Application to MR-Less Quantification
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Generation of Structural MR Images from Amyloid PET: Application to MR-Less Quantification

Choi, Hongyoon ; Lee, Dong Soo

Journal of Nuclear Medicine, 2018-07, Vol.59 (7), p.1111-1117 [Periódico revisado por pares]

United States: Society of Nuclear Medicine

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