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Olayinka Oladosu on Muck Rack

Olayinka Oladosu

As seen in: Nature, Frontiers
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Articles

High angular resolution diffusion imaging of neurodevelopment in children through data creation with deep learning

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By Olayinka Oladosu, Bryce Geeraert, Catherine Lebel, Yunyan Zhang, Fanny Lo
| Nature Verified
Abstract High-angular resolution diffusion imaging (HARDI) is an advanced method for characterizing brain microstructure and function. However, HARDI is time-consuming limiting real-world applications, especially in children. We aimed to address the challenge by creating non-acquired HARDI data through deep learning and testing utility in neurodevelopment. Brain diffusion magnetic resonance imaging from 95 children aged 2–10 years (49 females) were examined.
Open in Who Shared Issue with article?

CycleGAN models show consistent brain MRI synthesis across datasets supporting downstream tissue characterization in multiple sclerosis

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By Shayan Shahrokhi, Yunyan Zhang, Olayinka Oladosu, Rehman Tariq
| Frontiers
Abstract Background: Secondary quantitative analysis of brain magnetic resonance imaging (MRI) can provide valuable information for many neurological diseases, including multiple sclerosis (MS), but it demands complete datasets that are often unavailable clinically.
Open in Who Shared Issue with article?
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