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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,…

Optics · Physics 2020-11-11 Xianye Li , Yafei sun , Yikang He , Xun Li , Baoqing Sun

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…

Optics · Physics 2023-06-28 Yuhang Li , Yi Luo , Deniz Mengu , Bijie Bai , Aydogan Ozcan

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…

Optics · Physics 2022-05-23 Deniz Mengu , Aydogan Ozcan

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…

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…

Image and Video Processing · Electrical Eng. & Systems 2021-09-01 Fangshu Yang , Thanh-an Pham , Nathalie Brandenberg , Matthias P. Lutolf , Jianwei Ma , Michael Unser

Quantitative phase imaging (QPI) recovers the exact wavefront of light from the intensity measured by a camera. Topographical maps of translucent microscopic bodies can be extracted from these quantified phase shifts. We demonstrate…

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…

Optics · Physics 2019-09-04 Miu Tamamitsu , Keiichiro Toda , Ryoichi Horisaki , Takuro Ideguchi

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…

Image and Video Processing · Electrical Eng. & Systems 2020-12-02 Taean Chang , Youngju Jo , Gunho Choi , Donghun Ryu , Hyun-Seok Min , Yongkeun Park

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…

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.…

Optics · Physics 2020-07-21 Nathaniel Hai , Joseph Rosen

Electronic wave functions of planar molecules can be reconstructed via inverse Fourier transform of angle-resolved photoelectron spectroscopy (ARPES) data, provided the phase of the electron wave in the detector plane is known. Since the…

Other Condensed Matter · Physics 2016-09-23 Pavel Kliuiev , Tatiana Latychevskaia , Juerg Osterwalder , Matthias Hengsberger , Luca Castiglioni

Quantitative phase imaging (QPI) is a label-free technique providing both morphology and quantitative biophysical information in biomedicine. However, applying such a powerful technique to in vivo pathological diagnosis remains challenging.…

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…

Optics · Physics 2014-05-02 Xiaoze Ou , Roarke Horstmeyer , Changhuei Yang , Guoan Zheng

Recent advances in quantitative phase imaging (QPI) and artificial intelligence (AI) have opened up the possibility of an exciting frontier. The fast and label-free nature of QPI enables the rapid generation of large-scale and…

Computer Vision and Pattern Recognition · Computer Science 2018-07-16 YoungJu Jo , Hyungjoo Cho , Sang Yun Lee , Gunho Choi , Geon Kim , Hyun-seok Min , YongKeun Park

The Fourier inversion of phased coherent diffraction patterns offers images without the resolution and depth-of-focus limitations of lens-based tomographic systems. We report on our recent experimental images inverted using recent…

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…

Optics · Physics 2023-08-29 Che-Yung Shen , Jingxi Li , Deniz Mengu , Aydogan Ozcan

We propose and demonstrate a new phase retrieval method for imaging through random media. Although methods to recover the Fourier amplitude through random distortions are well established, recovery of the Fourier phase has been a more…

Optics · Physics 2021-05-14 Byungjae Hwang , Taeseong Woo , Cheolwoo Ahn , Jung-Hoon Park

Quaternionic signal processing provides powerful tools for efficiently managing color signals by preserving the intrinsic correlations among signal dimensions through quaternion algebra. In this paper, we address the quaternionic phase…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Ren Hu , Pan Lian

One of the most powerful approaches to imaging at the nanometer or subnanometer length scale is coherent diffraction imaging using X-ray sources. For amorphous (non-crystalline) samples, the raw data can be interpreted as the modulus of the…

Numerical Analysis · Mathematics 2020-04-02 Alexander Barnett , Charles L. Epstein , Leslie Greengard , Jeremy Magland
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