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English(EN) DeepFilters: Scattering-Aware Pupil Engineering with Learned Digital Filter Reconstruction for Extended Depth of Field Microscopy

DeepFilters 通过感知散射的光学器件增强显微镜景深

研究人员开发了 DeepFilters,一种用于显微镜的新型框架,通过工程化瞳孔滤波器并采用学习数字重建网络来增强景深。该系统设计为散射感知,使其即使在光散射会降低图像质量的生物组织中也能有效工作。DeepFilters 已证明其点扩散函数得到显著扩展,并能够在生物样本中恢复超过 120 微米的深度信号。 AI

影响 引入了一种新的计算成像技术,可以改善生物样本分析。

排序理由 该集群包含一篇详细介绍显微镜新技术框架的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CV 阅读 →

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DeepFilters 通过感知散射的光学器件增强显微镜景深

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Lei Tian ·

    DeepFilters: Scattering-Aware Pupil Engineering with Learned Digital Filter Reconstruction for Extended Depth of Field Microscopy

    Extended depth of field microscopy encodes axial information into a single acquisition through engineered point spread functions, but conventional and deep optics approaches are subject to degradation in scattering tissue. We introduce DeepFilters, a scattering-aware deep optics …