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Artificial intelligence–powered magnetic resonance imaging reconstruction: methods, challenges, and emerging trendshaih—a narrative review

   
@article{JMAI11313,
	author = {Anjana Joshi and Vettavalam Subramanian Krushnasamy},
	title = {Artificial intelligence–powered magnetic resonance imaging reconstruction: methods, challenges, and emerging trendshaih—a narrative review},
	journal = {Journal of Medical Artificial Intelligence},
	volume = {0},
	number = {0},
	year = {2026},
	keywords = {},
	abstract = {Artificial intelligence (AI), particularly deep learning, has revolutionized magnetic resonance imaging (MRI) reconstruction by accelerating acquisition and enhancing image quality. This narrative review synthesizes the most recent algorithmic advances, clinical translation efforts, and research gaps that shape the future of AI-powered MRI reconstruction.},
	issn = {2617-2496},	url = {https://jmai.amegroups.org/article/view/11313}
}