14 citations · 14 across the 7 of their papers we have counts for
10 papers
Generalizable fetal brain biometry via adaptive artificial intelligence
Yijin Li, Mingxuan Liu, Yi Liao +24
Reliable fetal brain biometry on magnetic resonance imaging (MRI) is essential for diagnosing congenital brain anomalies, but artificial intelligence models often lose accuracy und…
templar: agentic induction and evolution of standardized radiology reporting templates from large-scale clinical corpora
Xiaotian Hu, Mingxuan Liu, Zhonghan Wang +9
Structured radiology reporting mitigates the heterogeneity of free-text reports, yet its benefits depend on high-quality reporting templates. In practice, such templates are conven…
ASTAR: Automated induction of STAndardized radiology Reporting templates from large-scale clinical free-text corpora
Xinfeng Zhang, Mingxuan Liu, Yifei Chen +9
Structured reporting converts free-text radiology narratives into queryable data keys, facilitating cohort assembly, longitudinal tracking, and training label generation for medica…
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…
Annotation-free deep learning for detection and segmentation of fetal germinal matrix-intraventricular hemorrhage in brain MRI
Mingxuan Liu, Yingqi Hao, Yi Liao +17
Prenatal germinal matrix-intraventricular hemorrhage (GMH-IVH) is a leading cause of infant mortality and neurodevelopmental impairment, yet its manual diagnosis and lesion segment…
autoPET IV challenge: Incorporating organ supervision and human guidance for lesion segmentation in PET/CT
Junwei Huang, Yingqi Hao, Yitong Luo +6
Lesion Segmentation in PET/CT scans is an essential part of modern oncological workflows. To address the challenges of time-intensive manual annotation and high inter-observer vari…
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…
Artificial Intelligence for Neuro MRI Acquisition: A Review
Hongjia Yang, Guanhua Wang, Ziyu Li +7
Magnetic resonance imaging (MRI) has significantly benefited from the resurgence of artificial intelligence (AI). By leveraging AI's capabilities in large-scale optimization and pa…