Xinzhen Zhang

dblp:87/6570 · DBLP profile ↗
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4ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0001-7498-6616ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 3 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1
YearPublicationVenuePosition
2021 A semidefinite relaxation method for second-order cone tensor eigenvalue complementarity problems
Lulu Cheng, Xinzhen Zhang, Gu-Yan Ni
J. Glob. Optim.2
2020 Previous-stage-based ROI Reconstruction Method for Ultra-low-dose CT Angiography
abstract
Computed tomography angiography (CTA) is a powerful tool for the diagnosis of vascular diseases and its radiation dose is widely concerned. Limited scan within vessel region, deemed as region-of-interest (ROI), is a particularly apt dose reduction strategy for CTA since clinical assessment mainly depends on vessel structures. However, insufficient raw data may induce noise and artifacts in images reconstructed by conventional analytic and iterative methods. In this paper, we introduced an ultra-low-dose scan protocol for CTA, by modifying the contrast-enhanced stage with a low-mA, few-view ROI scan. Accordingly, a previous-stage-based ROI reconstruction method (PSBROI) was proposed with weighted projections and voxels and a dual-dictionary learning (DDL) strategy. Experiments showed that under the ultra-low-dose scan protocol, the proposed method performed better in artifact removal, noise suppression and structure preservation within ROI than the conventional methods. The ultra-low-dose scan with 30 mAs, 60 projection views and 34.1 mm ROI size could reduce dose to about 0.305% of normal dose.
Yufu Zhou, Xinzhen Zhang, Jianqi Sun, Jun Zhao 0010
BIBE2
2012 Standard bi-quadratic optimization problems and unconstrained polynomial reformulations
Immanuel M. Bomze, Chen Ling 0001, Liqun Qi 0001, Xinzhen Zhang
J. Glob. Optim.4
2011 Semidefinite relaxation bounds for bi-quadratic optimization problems with quadratic constraints
Xinzhen Zhang, Chen Ling 0001, Liqun Qi 0001
J. Glob. Optim.1