17 citations · 17 across the 8 of their papers we have counts for
10 papers
HAVIR: HierArchical Vision to Image Reconstruction using CLIP-Guided Versatile Diffusion
Shiyi Zhang, Dong Liang, Hairong Zheng +1
The reconstruction of visual information from brain activity fosters interdisciplinary integration between neuroscience and computer vision. However, existing methods still face ch…
HAVIR: HierArchical Vision to Image Reconstruction using CLIP-Guided Versatile Diffusion
Shiyi Zhang, Dong Liang, Hairong Zheng +1
Reconstructing visual information from brain activity bridges the gap between neuroscience and computer vision. Even though progress has been made in decoding images from fMRI usin…
Unsupervised patch-based dynamic MRI reconstruction using learnable tensor function with implicit neural representation
Yuanyuan Liu, Yuanbiao Yang, Jing Cheng +8
Dynamic MRI suffers from limited spatiotemporal resolution due to long acquisition times. Undersampling k-space accelerates imaging but makes accurate reconstruction challenging. S…
Accurate myocardial T1 mapping at 5T using an improved MOLLI method: A validation study
Linqi Ge, Yinuo Zhao, Yubo Guo +7
Background: Accurate myocardial T1 mapping at 5T remains a technical challenge due to field inhomogeneity and prolonged T1 values. The aim of this study is to develop an accurate a…
Myocardial T1 mapping at 5T using multi-inversion recovery real-time spoiled GRE
Linqi Ge, Yihang Zhang, Huibin Zhu +6
Objective: To develop an accurate myocardial T1 mapping technique at 5T using Look-Locker-based multiple inversion-recovery with the real-time spoiled gradient echo (GRE) acquisiti…
Guided MRI Reconstruction via Schrödinger Bridge
Yue Wang, Yuanbiao Yang, Zhuo-xu Cui +5
Magnetic Resonance Imaging (MRI) is an inherently multi-contrast modality, where cross-contrast priors can be exploited to improve image reconstruction from undersampled data. Rece…
Quantum Neural Network for Accelerated Magnetic Resonance Imaging
Shuo Zhou, Yihang Zhou, Congcong Liu +4
Magnetic resonance image reconstruction starting from undersampled k-space data requires the recovery of many potential nonlinear features, which is very difficult for algorithms t…
Pediatric TSC-Related Epilepsy Classification from Clinical MR Images Using Quantum Neural Network
Ling Lin, Yihang Zhou, Zhanqi Hu +8
Tuberous sclerosis complex (TSC) manifests as a multisystem disorder with significant neurological implications. This study addresses the critical need for robust classification mo…
Pathology-genomic fusion via biologically informed cross-modality graph learning for survival analysis
Zeyu Zhang, Yuanshen Zhao, Jingxian Duan +5
The diagnosis and prognosis of cancer are typically based on multi-modal clinical data, including histology images and genomic data, due to the complex pathogenesis and high hetero…
DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution
Shanshan Wang, Huitao Cheng, Leslie Ying +5
This paper proposes a multi-channel image reconstruction method, named DeepcomplexMRI, to accelerate parallel MR imaging with residual complex convolutional neural network. Differe…