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 (...

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Bibliographic Details
Main Authors: Zhou, Xiao, Qiu, Shangran, Joshi, Prajakta S, Xue, Chonghua, Killiany, Ronald J, Mian, Asim Z, Chin, Sang, Au, Rhoda, Kolachalama, Vijaya B
Other Authors: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Format: Article
Language:English
Published: BioMed Central 2022
Online Access:https://hdl.handle.net/1721.1/132063.2

Internet

https://hdl.handle.net/1721.1/132063.2

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