We theoretically and experimentally study the noise correlations in an array of lasers based on a VECSEL (Vertical External Cavity Surface Emitting Laser) architecture. The array of two or three lasers is created inside a planar degenerate cavity with a mask placed in a self-imaging position. Injection from each laser to its neighbors is created by diffraction, which creates a controllable complex coupling coefficient. The noise correlations between the different modes are observed to be dramatically different when the lasers are phase-locked or unlocked. These results are well explained by a rate equation model that takes into account the class-A dynamics of the lasers. This model permits the isolatation of the influence of the complex coupling coefficients and of the Henry α-factor on the noise behavior of the laser array.
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http://dx.doi.org/10.1364/OE.501051 | DOI Listing |
Jpn J Radiol
January 2025
Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan.
Purpose: To evaluate the effects of four-dimensional noise reduction filtering using a similarity algorithm (4D-SF) on the image quality and tumor visibility of low-dose dynamic computed tomography (CT) in evaluating breast cancer.
Materials And Methods: Thirty-four patients with 38 lesions who underwent low-dose dynamic breast CT and were pathologically diagnosed with breast cancer were enrolled. Dynamic CT images were reconstructed using iterative reconstruction alone or in combination with 4D-SF.
Comput Biol Med
January 2025
University of Rwanda, Rwanda. Electronic address:
Deep learning methods have significantly improved medical image analysis, particularly in detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some drawbacks, such as limited interpretability, extensive computational resources, and the need for extensive datasets. To tackle these issues, we introduced two novel algorithms: the Dynamic Co-Occurrence Grey Level Matrix (DC-GLM) and the Contextual Adaptation Multiscale Gabor Network (CAMSGNeT).
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
Faculty of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa, Israel.
Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection of metastatic tumors and response to therapy assessment due to its high sensitivity compared to anatomical imaging modalities. The balance between image quality and radiation exposure is critical, as reducing the administered dose results in a lower signal-to-noise ratio (SNR) and information loss, which may significantly affect clinical diagnosis. Deep learning (DL) algorithms have recently made significant progress in low-dose (LD) PET reconstruction.
View Article and Find Full Text PDFJ Neurosci
January 2025
Department of Mathematics, Polytechnic University of Catalonia, Spain.
The brain's activity fluctuations have different temporal scales across the brain regions, with associative regions displaying slower timescales than sensory areas. This so-called hierarchy of timescales has been shown to correlate with both structural brain connectivity and intrinsic regional properties. Here, using publicly available human resting-state fMRI and dMRI data it was found that, while more structurally connected brain regions presented activity fluctuations with longer timescales, their activity fluctuations presented lower variance.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, Rensselaer, New York, United States of America.
Since the emergence of the SARS-CoV-2 virus, research into the existence, extent, and pattern of seasonality has been of the highest importance for public health preparation. This study uses a novel bandpass bootstrap approach called the Variable Bandpass Periodic Block Bootstrap to investigate the periodically correlated components including seasonality within US COVID-19 mortality. Bootstrapping to produce confidence intervals for periodic characteristics such as the seasonal mean requires preservation of the periodically correlated component's correlation structure during resampling.
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