Author

Hong-Hsi Lee

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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. · NeuroImage · 0 citations

Open access Aug 2026

Clinical Soma and Neurite Density Imaging (SANDI): Translational Microstructure Mapping on Clinical 3T MRI Scanners.

PURPOSE The Soma and Neurite Density Imaging (SANDI) model enables characterization of gray matter (GM) microstructure by estimating soma and neurite signal fractions, but its clinical applicability is limited by the need for multi-shell acquisitions (at least five b-values up to 6000 s/mm2), requiring high-gradient MR...

Hansol Lee, Kwok-Shing Chan, Yixin Ma et al. · Magnetic Resonance in Medici... · 0 citations

Sep 2026

Microstructural Characterization of Functional Network-Based Neurodegeneration in Multiple Sclerosis Using High-Gradient Diffusion MRI.

BACKGROUND AND PURPOSE Neurodegeneration is a key component of clinical disability in multiple sclerosis (MS). However, the underlying mechanism of localized gray matter (GM) atrophy in MS remains unknown. More recently, a network-based etiology has been postulated, which may be associated with clinical progression. Th...

Florence L. Chiang, Eva A. Krijnen, Diana A. Hobbs et al. · AJNR. American journal of ne... · 0 citations