Enhancing magnetic resonance imaging-driven Alzheimer's disease classification performance using generative adversarial learning

Enhancing magnetic resonance imaging-driven Alzheimer's disease classification performance using generative adversarial learning

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Abstract Background Generative adversarial networks (GAN) can produce images of improved quality but their ability to augment image-based classification is not fully explored. We evaluated if a modified GAN can learn from magnetic resonance imaging (MRI) scans of multiple magnetic field strengths to...

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Bibliographic Details
Main Authors:	Zhou, Xiao (Author), Qiu, Shangran (Author), Joshi, Prajakta S (Author), Xue, Chonghua (Author), Killiany, Ronald J (Author), Mian, Asim Z (Author), Chin, Sang (Author), Au, Rhoda (Author), Kolachalama, Vijaya B (Author)
Other Authors:	Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences (Contributor)
Format:	Article
Language:	English
Published:	BioMed Central, 2022-07-15T20:36:32Z.
Subjects:	Article
Online Access:	Get fulltext

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