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Fourier ptychographic microscopy (FPM) is a recently developed imaging modality that uses angularly varying illumination to extend a system performance beyond the limit defined by its optical elements. The FPM technique applies a novel…

光学 · 物理学 2014-05-02 Xiaoze Ou , Roarke Horstmeyer , Changhuei Yang , Guoan Zheng

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

Quantitative phase microscopy (QPM) is a label-free technique that enables to monitor morphological changes at subcellular level. The performance of the QPM system in terms of spatial sensitivity and resolution depends on the coherence…

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

Quantitative phase microscopy (QPM), a technique combining phase imaging and microscopy, enables visualization of the 3D topography in reflective samples, as well as the inner structure or refractive index distribution of transparent and…

光学 · 物理学 2025-01-17 Vicente Mico , Juanjuan Zheng , Javier Garcia , Zeev Zalevsky , Peng Gao

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) 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) quantifies the sample-specific optical-phase-delay enabling objective studies of optically-transparent specimens such as biological samples, but lacks chemical sensitivity limiting its application to…

光学 · 物理学 2019-09-04 Miu Tamamitsu , Keiichiro Toda , Ryoichi Horisaki , Takuro Ideguchi

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…

We demonstrate a new computational illumination technique that achieves large space-bandwidth-time product, for quantitative phase imaging of unstained live samples in vitro. Microscope lenses can have either large field of view (FOV) or…

光学 · 物理学 2015-10-16 Lei Tian , Ziji Liu , Li-Hao Yeh , Michael Chen , Jingshan Zhong , Laura Waller

As a label-free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials science, and engineering. Multispectral QPI measures…

光学 · 物理学 2023-08-29 Che-Yung Shen , Jingxi Li , Deniz Mengu , Aydogan Ozcan

Quantitative susceptibility mapping (QSM) is an MRI phase-based post-processing method that quantifies tissue magnetic susceptibility distributions. However, QSM acquisitions are relatively slow, even with parallel imaging. Incoherent…

图像与视频处理 · 电气工程与系统科学 2021-07-20 Yang Gao , Martijn Cloos , Feng Liu , Stuart Crozier , G. Bruce Pike , Hongfu Sun

Quantitative phase imaging (QPI) is important in many applications such as microscopy and crystallography. To quantitatively reveal phase information, people could either employ interference to map phase distribution into intensity fringes,…

光学 · 物理学 2020-11-11 Xianye Li , Yafei sun , Yikang He , Xun Li , Baoqing Sun

The trade-off between throughput and image quality is an inherent challenge in microscopy. To improve throughput, compressive imaging under-samples image signals; the images are then computationally reconstructed by solving a regularized…

图像与视频处理 · 电气工程与系统科学 2023-03-07 Udith Haputhanthri , Andrew Seeber , Dushan Wadduwage

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…

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…

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

Cell segmentation in single-shot quantitative phase microscopy (ssQPM) faces challenges from traditional thresholding methods that are sensitive to noise and cell density, while deep learning approaches using simple channel concatenation…

计算机视觉与模式识别 · 计算机科学 2025-11-04 Rajatsubhra Chakraborty , Ana Espinosa-Momox , Riley Haskin , Depeng Xu , Rosario Porras-Aguilar

This article presents a thorough comparison of themain QPM techniques, focusing on their accuracy in terms of measurement precision and trueness. We focus on 8 techniques, namely digital holographic microscopy (DHM), cross-grating wavefront…

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
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