Dataset Information

High-Definition Optophysical Image Construction Using Mosaics of Pixelated Wrinkles.

ABSTRACT: Despite many efforts in structuring surfaces using mechanical instabilities, the practical application of these structures to advanced devices remains a challenging task due to the limited capability to control the local morphology. A platform that programs the orientation of mechanically anisotropic molecules is demonstrated; thus, the surface wrinkles, promoted by such instabilities, can be patterned in the desired manner. The optics based on a spatial light modulator assembles wrinkle pixels of a notably small dimension over a large area at fast fabrication speed. Furthermore, these pixelated wrinkles can be formed on curved geometries. The pixelated wrinkles can record images, which are naturally invisible, by mapping the gray level to the orientation of wrinkles. They can retrieve those images using the patterned optical phase retardation generated under the crossed polarizers. As a result, it is shown that the pixelated wrinkles enable new applications in optics such as image storage, informative labeling, and anti-counterfeiting.

SUBMITTER: Kim K

PROVIDER: S-EPMC7740086 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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High-Definition Optophysical Image Construction Using Mosaics of Pixelated Wrinkles.

Kim Kitae K Kim Se-Um SU Choi Subi S Heo Kyuyoung K Ahn Suk-Kyun SK Na Jun-Hee JH

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20201026 24

Despite many efforts in structuring surfaces using mechanical instabilities, the practical application of these structures to advanced devices remains a challenging task due to the limited capability to control the local morphology. A platform that programs the orientation of mechanically anisotropic molecules is demonstrated; thus, the surface wrinkles, promoted by such instabilities, can be patterned in the desired manner. The optics based on a spatial light modulator assembles wrinkle pixels ...[more]

PMID: 33344125

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Project description:BackgroundThe high-definition standard (HD-standard) scan mode has been proven to display stents better than the standard (STND) scan mode but with more image noise. Deep learning image reconstruction (DLIR) is capable of reducing image noise. This study examined the impact of HD-standard scan mode with DLIR algorithms on stent and coronary artery image quality in coronary computed tomography angiography (CCTA) via a comparison with conventional STND scan mode and adaptive statistical iterative reconstruction-Veo (ASIR-V) algorithms.MethodsThe data of 121 patients who underwent HD-standard mode scans (group A: N=47, with coronary stent) or STND mode scans (group B: N=74, without coronary stent) were retrospectively collected. All images were reconstructed with ASIR-V at a level of 50% (ASIR-V50%) and a level of 80% (ASIR-V80%) and with DLIR at medium (DLIR-M) and high (DLIR-H) levels. The noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), artifact index (AI), and in-stent diameter were measured as objective evaluation parameters. Subjective assessment involved a 5-point scale for overall image quality, image noise, stent appearance, stent artifacts, vascular sharpness, and diagnostic confidence. Diagnostic confidence was evaluated based on the presence or absence of significant stenosis (≥50% lumen reduction). Both subjective and objective evaluations were conducted by two radiologists independently, with kappa and intraclass correlation statistics being used to test the interobserver agreement.ResultsThere were 76 evaluable stents in group A, and the DLIR-H algorithm significantly outperformed other algorithms, demonstrating the lowest noise (41.6±7.1/41.3±7.2) and AI (32.4±8.9/31.2±10.1), the highest SNR (14.6±3.5/15.0±3.5) and CNR (13.6±3.8/13.9±3.8), and the largest in-stent diameter (2.18±0.61/2.19±0.61) in representing true stent diameter (all P values <0.01), as well as the highest score in each subjective evaluation parameter. In group B, a total of 296 coronary arteries were evaluated, and the DLIR-H algorithm provided the best objective image quality, with statistically superior noise, SNR, and CNR compared with the other algorithms (all P values <0.05). Moreover, the HD-standard mode scan with DLIR provided better image quality and a lower radiation dose than did the STND mode scan with ASIR-V (P<0.01).ConclusionsHD-standard scan mode with DLIR-H improves image quality of both stents and coronary arteries on CCTA under a lower radiation dose.

Dataset Information

High-Definition Optophysical Image Construction Using Mosaics of Pixelated Wrinkles.

Publications

High-Definition Optophysical Image Construction Using Mosaics of Pixelated Wrinkles.

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