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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) 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

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 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) 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) 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

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…

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

This paper reported a general noninterferometric high-accuracy quantitative phase imaging (QPI) method for arbitrary complex valued objects. Given by a typical 4f optical configuration as the imaging system, three frames of small-window…

Image and Video Processing · Electrical Eng. & Systems 2021-05-05 Jianhui Huang , An Pan , Huiliang Jin , Guoxiang Meng , Qian Ye

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.…

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

In this work, we present a highly efficient quantitative phase imaging (QPI) approach using programmable annular LED illumination based on traditional bright-field microscope. As a new type of coded illumination, the LED array provides a…

Optics · Physics 2017-07-14 Jiaji Li , Qian Chen , Jialin Zhang , Yan Zhang , Linpeng Lu , Chao Zuo

We introduce the white light quantitative phase imaging unit (WQPIU) as a practical realization of quantitative phase imaging (QPI) on standard microscope platforms. The WQPIU is a compact stand-alone unit which measures sample induced…

Optics · Physics 2016-05-04 YoonSeok Baek , KyeoReh Lee , Jonghee Yoon , Kyoohyun Kim , YongKeun Park

Quantitative phase imaging (QPI) is often used for label-free single cell analysis with its high-contrast images of optical phase delay (OPD) map. Contrary to other imaging methods, sensitivity improvement has not been intensively explored…

Optics · Physics 2025-05-06 Keiichiro Toda , Miu Tamamitsu , Takuro Ideguchi

Quantitative phase imaging (QPI) enables label-free, high-contrast visualization of transparent specimens, but its common implementation in off-axis digital holographic microscopy (DHM) requires a separate reference beam, which increases…

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…

Complex-field imaging is indispensable for numerous applications at wavelengths from X-ray to THz, with amplitude describing transmittance (or reflectivity) and phase revealing intrinsic structure of the target object. Coherent diffraction…

Image and Video Processing · Electrical Eng. & Systems 2021-04-07 Meng Li , Liheng Bian , Guoan Zheng , Andrew Maiden , Yang Liu , Yiming Li , Qionghai Dai , Jun Zhang

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

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

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
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