Lijuan Zhang
Chinese Academy of Sciences
59 Papers
104 Citations
Lijuan Zhang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 19, co-authored 45 publications. Previous affiliations of Lijuan Zhang include Cornell University & Icahn School of Medicine at Mount Sinai.
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Papers
Noncontrast MRA of Pedal Arteries in Type II Diabetes : Effect of Disease Load on Vessel Visibility
TL;DR: FSD-SSFP proved to be a useful modality of NC-MRA for pedal artery imaging in diabetic patients and the effect of disease load of type II diabetes on the vessel depiction was explored.
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DLNLF-net: Denoised local and non-local deep features fusion network for malignancy characterization of hepatocellular carcinoma
TL;DR: In this article , a denoised local and non-local deep features fusion network (DLNLF-net) was proposed for grading hepatocellular carcinoma (HCC).
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Bifurcation Analysis on the Periodic Response of a Comb Drive MEMS Resonator
TL;DR: In this article , the authors investigated the bifurcation characteristics of a comb drive MEMS resonator and used the method of averaging and the residue theorem to get a more accurate analytical solution for the periodic response.
High spatiotemporal resolution fMRI using partial separability model.
Caiyun Shi,Guoxi Xie,Xiaoyong Zhang,Xiaoyong Zhang,Shi Su,Yongqin Zhang,Lijuan Zhang,Bensheng Qiu,Xin Liu +8 more
TL;DR: (k-t) space data is sparsely acquired and reconstructed for BOLD fMRI using a partial separability (PS) model with a ℓ2-norm constraint, which achieves a high temporal resolution of 200 ms without compromising spatial resolution.
Inter-Modal Conditional-Guided Fusion Network with Transformer for Grading Hepatocellular Carcinoma
Shangxuan Li,Yanshu Fang,Guangyi Wang,Lijuan Zhang,Wu Zhou +4 more
- 18 Apr 2023
TL;DR: The experimental results of the clinical hepatocellular carcinoma (HCC) dataset show that the proposed inter-modal conditional-guided fusion network with Transformer (ICF-Former) is superior to the previously reported multimodal fusion methods for HCC grading.
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