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Enhancing magnetic resonance imaging-driven Alzheimer’s disease classification performance using generative adversarial learning
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 enhance...
Autores principales: | Zhou, Xiao, Qiu, Shangran, Joshi, Prajakta S., Xue, Chonghua, Killiany, Ronald J., Mian, Asim Z., Chin, Sang P., Au, Rhoda, Kolachalama, Vijaya B. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7958452/ https://www.ncbi.nlm.nih.gov/pubmed/33715635 http://dx.doi.org/10.1186/s13195-021-00797-5 |
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