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相关论文: Deep Phase Shifter for Quantitative Phase Imaging

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Multi-spectral quantitative phase imaging (MS-QPI) is a cutting-edge label-free technique to determine the morphological changes, refractive index variations and spectroscopic information of the specimens. The bottleneck to implement this…

Complex field imaging, which captures both the amplitude and phase information of input optical fields or objects, can offer rich structural insights into samples, such as their absorption and refractive index distributions. However,…

光学 · 物理学 2024-05-30 Jingxi Li , Yuhang Li , Tianyi Gan , Che-Yung Shen , Mona Jarrahi , Aydogan Ozcan

Deep neural networks have emerged as effective tools for computational imaging including quantitative phase microscopy of transparent samples. To reconstruct phase from intensity, current approaches rely on supervised learning with training…

图像与视频处理 · 电气工程与系统科学 2020-01-28 Emrah Bostan , Reinhard Heckel , Michael Chen , Michael Kellman , Laura Waller

Phase recovery from intensity-only measurements forms the heart of coherent imaging techniques and holography. Here we demonstrate that a neural network can learn to perform phase recovery and holographic image reconstruction after…

计算机视觉与模式识别 · 计算机科学 2017-12-13 Yair Rivenson , Yibo Zhang , Harun Gunaydin , Da Teng , Aydogan Ozcan

We present a data-driven approach to compensate for optical aberration in calibration-free quantitative phase imaging (QPI). Unlike existing methods that require additional measurements or a background region to correct aberrations, we…

图像与视频处理 · 电气工程与系统科学 2020-12-02 Taean Chang , Youngju Jo , Gunho Choi , Donghun Ryu , Hyun-Seok Min , Yongkeun Park

Quantitative phase imaging (QPI) is a label-free computational imaging technique that provides optical path length information of specimens. In modern implementations, the quantitative phase image of an object is reconstructed digitally…

光学 · 物理学 2022-05-23 Deniz Mengu , Aydogan Ozcan

Quantitative phase imaging (QPI) is a label-free computational imaging technique used in various fields, including biology and medical research. Modern QPI systems typically rely on digital processing using iterative algorithms for phase…

光学 · 物理学 2023-06-28 Yuhang Li , Yi Luo , Deniz Mengu , Bijie Bai , Aydogan Ozcan

White light phase-shifting interference microscopy (WL-PSIM) is a prominent technique for high-resolution quantitative phase imaging (QPI) of industrial and biological specimens. However, multiple interferograms with accurate phase-shifts…

图像与视频处理 · 电气工程与系统科学 2021-05-04 Sunil Bhatt , Ankit Butola , Sheetal Raosaheb Kanade , Anand Kumar , Dalip Singh Mehta

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse…

Quantitative phase imaging (QPI) is a label-free technique that provides optical path length information for transparent specimens, finding utility in biology, materials science, and engineering. Here, we present quantitative phase imaging…

Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase…

图像与视频处理 · 电气工程与系统科学 2021-09-01 Fangshu Yang , Thanh-an Pham , Nathalie Brandenberg , Matthias P. Lutolf , Jianwei Ma , Michael Unser

The ghost imaging (GI) technique, which has attracted attention as a highly sensitive and noise-resistant technique, employs a spatially modulated illuminating light and a single-pixel detector. Generally, the information acquired by GI is…

光学 · 物理学 2025-05-23 Shuhei Yoshida

Interferometric imaging is a well established method to image phase objects by mixing the image wavefront with a reference one on a CCD camera. It has also been applied to fast transient phenomena, mostly through the analysis of single…

While characterization of coherent wavefields is essential to laser, x-ray and electron imaging, sensors measure the squared magnitude of the field, rather than the field itself. Holography or phase retrieval must be used to characterize…

图像与视频处理 · 电气工程与系统科学 2020-12-10 David J. Brady , Timothy J. Schulz , Chengyu Wang

Interferometry can measure the shape or the material density of a system that could not be measured otherwise by recording the difference between the phase change of a signal and a reference phase. This difference is always between $-\pi$…

等离子体物理 · 物理学 2022-10-20 Pierre-Alexandre Gourdain , Aidan Bachmann

Quantitative phase imaging (QPI) enables visualization and quantitative extraction of the optical phase information of transparent samples. However, conventional QPI techniques typically rely on multi-frame acquisition or complex…

光学 · 物理学 2025-12-02 Xiangjiang Bao , Zheng-da Hu , Lucas Kreiss , Josh Lerner , Roarke Horstmeyer

In the last five decades, iterative phase retrieval methods draw large amount of interest across the research community as a non-interferometric approach to recover quantitative phase distributions from one (or more) intensity measurement.…

光学 · 物理学 2020-07-21 Nathaniel Hai , Joseph Rosen

Quantitative phase imaging (QPI) has been widely applied in characterizing cells and tissues. Spatial light interference microscopy (SLIM) is a highly sensitive QPI method, due to its partially coherent illumination and common path…

图像与视频处理 · 电气工程与系统科学 2024-06-12 Yuheng Jiao , Yuchen R. He , Mikhail E. Kandel , Xiaojun Liu , Wenlong Lu , Gabriel Popescu

Quantitative phase imaging (QPI) through multi-core fibers (MCFs) has been an emerging in vivo label-free endoscopic imaging modality with minimal invasiveness. However, the computational demands of conventional iterative phase retrieval…

Conventional optical coherent receivers capture the full electrical field, including amplitude and phase, of a signal waveform by measuring its interference against a stable continuous-wave local oscillator (LO). In optical coherent…

信号处理 · 电气工程与系统科学 2020-06-24 Haoshuo Chen , Nicolas K. Fontaine , Joan M. Gene , Roland Ryf , David T. Neilson , Gregory Raybon
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