We report the first (to our knowledge) far-field ghost images formed with phase-sensitive classical-state light and compare them with ghost images of the same object formed with conventional phase-insensitive classical-state light. To generate signal and reference beams with phase-sensitive cross correlation, we used a pair of synchronized spatial light modulators that imposed random, spatially varying, anticorrelated phase modulation on the outputs from 50-50 beam splitting of a laser beam. In agreement with theory, we found the phase-sensitive image to be inverted, whereas the phase-insensitive image is erect, with both having comparable spatial resolutions and signal-to-noise ratios.
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http://dx.doi.org/10.1364/OL.36.003684 | DOI Listing |
Sensors (Basel)
January 2025
National Key Laboratory of Multispectral Information Intelligent Processing Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430000, China.
Despite rapid progress in UAV-based infrared vehicle detection, achieving reliable target recognition remains challenging due to dynamic viewpoint variations and platform instability. The inherent limitations of infrared imaging, particularly low contrast ratios and thermal crossover effects, significantly compromise detection accuracy. Moreover, the computational constraints of edge computing platforms pose a fundamental challenge in balancing real-time processing requirements with detection performance.
View Article and Find Full Text PDFMolecules
December 2024
Laboratory of Clinical Chemistry, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45110 Ioannina, Greece.
Coronary heart disease (CHD) is the leading cause of morbidity and mortality worldwide despite significant improvements in diagnostic modalities. Emerging evidence suggests that erythrocytes, or red blood cells (RBCs), are one of the most important contributors to the events implicated in atherosclerosis, although the molecular mechanisms behind it are under investigation. We used NMR-based lipidomic technology to investigate the RBC lipidome in patients with CHD compared to those with normal coronary arteries (NCAs), all angiographically documented, and its correlation with coronary artery stenosis.
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
University of Gothenburg, Bruna stråket 13, Goteborg, 405 30, SWEDEN.
Dual-polarity readout is a simple and robust way to mitigate Nyquist ghosting in diffusion-weighted echo-planar imaging but imposes doubled scan time. We here propose how dual-polarity readout can be implemented with little or no increase in scan time by exploiting an observed b-value dependence and signal averaging. The b-value dependence was confirmed in healthy volunteers with distinct ghosting at low b-values but of negligible magnitude at b = 1000 s/mm2.
View Article and Find Full Text PDFCells
December 2024
Research Center for Advanced Science and Technology, University of Tokyo, Tokyo 153-8904, Japan.
Imaging flow cytometry is a technology that performs microscopy image analysis of cells within flow cytometry and allows high-throughput, high-content cell analysis based on their intracellular molecular distribution and/or cellular morphology. While the technology has been available for a couple of decades, it has recently gained significant attention as technical limitations for higher throughput, sorting capability, and additional imaging dimensions have been overcome with various approaches. These evolutions have enabled imaging flow cytometry to offer a variety of solutions for life science and medicine that are not possible with conventional flow cytometry or microscopy-based screening.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha, 410004, Hunan, China.
Accurate segmentation of retinal blood vessels from retinal images is crucial for detecting and diagnosing a wide range of ophthalmic diseases. Our retinal blood vessel segmentation algorithm enhances microfine vessel extraction, improves edge texture clarity, and normalizes vessel distribution. It stabilizes neural network training for complex retinal vascular features.
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