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Author

B. Bilgiç

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Open access Sep 2026

Improving the accessibility of deep learning-based denoising for accelerated brain MRI using self-supervised learning and/or transfer learning.

The quality of human brain magnetic resonance imaging (MRI) is often compromised by noise. Deep learning-based image denoising methods using convolutional neural networks (CNNs) have proven to be more effective compared to conventional denoising methods. Nonetheless, most CNN-based denoising methods are not accessible...

Zi-Han Li, Zi-Yu Li, Ming-Xuan Liu et al. · 0 citations
Open access 2026

Brain Amyloid Burden Mapping Using MR Fingerprinting Aided by Deep Learning.

The proposed framework enables non-invasive Aβ mapping using a clinically feasible MRI protocol and may support repeated assessment for monitoring during anti-amyloid treatment.

Shohei Fujita, Y. Fushimi, Y. Otsuka et al. · 0 citations
Open access Aug 2026

An Open‐Source, Reproducible MRI Data Acquisition and Reconstruction Workflow Using Pulseq: Multi‐Site and Cross‐Vendor Validation

An open-source MRI workflow that harmonizes data acquisition, formatting, and reconstruction across sites and vendors is established, a critical step toward fully open and reproducible MRI, facilitating transparency, standardization, and collaboration across the research community.

Qing-Ping Chen, Thomas H. M. Roos, Amaya Murguia et al. · 0 citations

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