4 papers
A physics-informed foundation model for quantitative diffusion MRI
Zihan Li, Jialan Zheng, Ziyu Li +18
Understanding the human brain requires access to its microscopic tissue architecture. Diffusion magnetic resonance imaging (MRI) provides the only noninvasive window into whole-bra…
CoilDrop-MRI: Self-supervised physics-guided MRI reconstruction with coil dropout
Tongxi Song, Ziyu Li, Zihan Li +6
Self-supervised deep learning-based methods have shown great promise for accelerated magnetic resonance imaging (MRI) reconstruction, achieving high image quality without requiring…
INFANiTE: Implicit Neural representation for high-resolution Fetal brain spatio-temporal Atlas learNing from clinical Thick-slicE MRI
Xiaotian Hu, Mingxuan Liu, Hongjia Yang +10
Spatio-temporal fetal brain atlases are important for characterizing normative neurodevelopment and identifying congenital anomalies. However, existing atlas construction pipelines…
Enhance the Image: Super Resolution using Artificial Intelligence in MRI
Ziyu Li, Zihan Li, Haoxiang Li +5
This chapter provides an overview of deep learning techniques for improving the spatial resolution of MRI, ranging from convolutional neural networks, generative adversarial networ…