Here we demonstrate a long-depth-of-focus imaging method using polarization sensitive optical coherence tomography (PS-OCT). This method involves a combination of Fresnel-diffraction-model-based phase sensitive computational refocusing and Jones-matrix based PS-OCT (JM-OCT). JM-OCT measures four complex OCT images corresponding to four polarization channels. These OCT images are computationally refocused as preserving the mutual phase consistency. This method is validated using a static phantom, postmortem zebrafish, and porcine muscle samples. All the samples demonstrated successful computationally-refocused birefringence and degree-of-polarization-uniformity (DOPU) images. We found that defocusing induces polarization artifacts, i.e., incorrectly high birefringence values and low DOPU values, which are substantially mitigated by computational refocusing.
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http://dx.doi.org/10.1364/BOE.454975 | DOI Listing |
Soc Sci Med
January 2025
The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China. Electronic address:
Background: Anchoring in the socio-ecological framework and the differential impact theory, the present study pioneered to explore the differential network structures of multilevel risk and protective factors that influence depression among Chinese urban and rural adolescents.
Method: A sample of 684 urban adolescents and 1123 rural adolescents completed a battery of self-report questionnaires measuring their depressive symptoms, as well as risk and protective factors at intrapersonal (psychological flexibility, emotion regulation), interpersonal (social support, parental control), and social levels (social capital, stressful life events).
Results: Central risk and protective factors in both groups included psychological flexibility, which bridged intrapersonal, interpersonal and social resources, along with social support, social capital, rumination, catastrophizing, and self-blame.
Light-field imaging is widely used in many fields, such as computer vision, graphics, and microscopy imaging, to record high-dimensional light information for abundant visual perception. However, light-field imaging systems generally have high system complexity and limited resolution. Over the last decades, lensless imaging systems have attracted tremendous attention to alleviate the restrictions of lens-based architectures.
View Article and Find Full Text PDFDeep neural network (DNN) models, particularly convolutional neural networks (CNNs), have demonstrated remarkable performance in biomedical image classification due to their ability to automatically learn features from large datasets. One common challenge in the preparation of large, microscopic datasets for DNN tasks is sample defocusing, potentially impairing the model performance. To handle defocusing, computational imaging, or specifically quantitative phase imaging (QPI), performs digital refocusing by using both the phase and the amplitude of the complex optical field.
View Article and Find Full Text PDFNMR Biomed
January 2025
Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
P magnetic resonance spectroscopy (MRS) can spectrally resolve metabolites involved in phospholipid metabolism whose levels are altered in many cancers. Ultra-high field facilitates the detection of phosphomonoesters (PMEs) and phosphodiesters (PDEs) with increased SNR and spectral resolution. Utilizing multi-echo MR spectroscopic imaging (MRSI) further enhances SNR and enables T information estimation per metabolite.
View Article and Find Full Text PDFAPL Bioeng
September 2024
Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Italian National Research Council (ISASI-CNR), Italy.
Lab-on-a-Chip microfluidic devices present an innovative and cost-effective platform in the current trend of miniaturization and simplification of imaging flow cytometry; they are excellent candidates for high-throughput single-cell analysis. In such microfluidic platforms, cell tracking becomes a fundamental tool for investigating biophysical processes, from intracellular dynamics to the characterization of cell motility and migration. However, high-throughput and long-term cell tracking puts a high demand on the consumption of computing resources.
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