Zhang, Yiyao 
ORCID: 0000-0003-1166-6935, Chen, Ke ORCID: 0000-0002-6093-6623 and Yang, Shang Hua
(2024)
Breaking the Limitations with Sparse Inputs by Variational Frameworks (BLIss) in Terahertz Super-Resolution 3D Reconstruction.
Optics Express, 32 (9).
p. 15078.
Abstract
<jats:p>Data acquisition, image processing, and image quality are the long-lasting issues for terahertz (THz) 3D reconstructed imaging. Existing methods are primarily designed for 2D scenarios, given the challenges associated with obtaining super-resolution (SR) data and the absence of an efficient SR 3D reconstruction framework in conventional computed tomography (CT). Here, we demonstrate BLIss, a new approach for THz SR 3D reconstruction with sparse 2D data input. BLIss seamlessly integrates conventional CT techniques and variational framework with the core of the adapted Euler-Elastica-based model. The quantitative 3D image evaluation metrics, including the standard deviation of Gaussian, mean curvatures, and the multi-scale structural similarity index measure (MS-SSIM), validate the superior smoothness and fidelity achieved with our variational framework approach compared with conventional THz CT modal. Beyond its contributions to advancing THz SR 3D reconstruction, BLIss demonstrates potential applicability in other imaging modalities, such as X-ray and MRI. This suggests extensive impacts on the broader field of imaging applications.</jats:p>
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Bioengineering, Biomedical Imaging |
| Divisions: | Faculty of Science and Engineering > School of Physical Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 09 Apr 2024 07:29 |
| Last Modified: | 01 May 2024 13:09 |
| DOI: | 10.1364/oe.510670 |
| Open Access URL: | https://doi.org/10.1364/OE.510670 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3180144 |
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