Single-shot phase contrast microscopy using polarisation-resolved differential phase contrast

Kalita, Ranjan; Flanagan, W.; Lightley, Jonathan; Kumar, Sunil; Alexandrov, Yuriy; García, Edwin; Hintze, Mark; Barkoulas, Michalis; Dunsby, Chris; French, P. M. W.

doi:10.1101/2021.04.14.437846

Cited by 2 publications

(2 citation statements)

References 10 publications

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“…We note that polarization cameras can also be used for labelfree microscopy (66,67) such as single-shot phase contrast microscopy (68) and polarization-sensitive Fourier ptychography (69), leaving the possibility for multiplexing of fluorescence and label-free techniques. Overall, we envisage that the combination of POLCAM's simple implementation and ease of use, computational speed, and open-source software will lead to new biological insight across diverse systems.…”

Section: Discussionmentioning

confidence: 99%

POLCAM: Instant molecular orientation microscopy for the life sciences

Bruggeman

Zhang

Needham

et al. 2023

Preprint

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Current methods for single-molecule orientation localization microscopy (SMOLM) require optical setups and algorithms that can be prohibitively slow and complex, limiting the widespread adoption for biological applications. We present POLCAM, a simplified SMOLM method based on polarized detection using a polarization camera, that can be easily implemented on any wide-field fluorescence microscope. To make polarization cameras compatible with single-molecule detection, we developed theory to minimize field-of-view errors, used simulations to optimize experimental design, and developed a fast algorithm based on Stokes parameter estimation which can operate over 1000 fold faster than the state of the art, enabling near-instant determination of molecular anisotropy. To aid in the adoption of POLCAM, we developed open-source image analysis software; a napari plugin for visualization of high-dimensional diffraction-limited polarization camera datasets, and a website detailing hardware installation and software use. To illustrate the potential of POLCAM in the life sciences, we applied our method to study both alpha-synuclein fibrils and the actin cytoskeleton of mammalian cells. To demonstrate that POLCAM also allows diffraction-limited imaging, we demonstrate POLCAM imaging actin in fibroblast-like cells and the plasma membrane of live human T cells.

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Section: Discussionmentioning

confidence: 99%

POLCAM: Instant molecular orientation microscopy for the life sciences

Bruggeman

Zhang

Needham

et al. 2023

Preprint

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“…Zhao, Ming et al have tried modeling the LED array position deviation into neural network, but the optimization process is very time-consuming [25]. Since using physical means to reduce the morbidity of inverse problems is a very effective method [26,27,28], we have reduced the pathologicality of phase recovery problems through inserting a wedge angle in front of the microscope to imporve the speed and quality of reconstruction [29].In this paper, in order to reduce the pathological degree of reconstruction problem, we turn to find physical method to correct LED array position deviation. We choose four brightfield to darkfield transition LR images which located on orthogonal direction, using boundary of bright-field to dark-field transition on the LR images to calculate LED array position deviation inspired by the method proposed in reference [3].…”

Section: Introductionmentioning

confidence: 99%

Fourier ptychography multi-parameter neural network with composite physical priori optimization

Yang¹,

Zhang²,

Zheng³

et al. 2022

Preprint

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Fourier ptychography microscopy(FP) is a recently developed computational imaging approach for microscopic super-resolution imaging. By turning on each light-emitting-diode (LED) located on different position on the LED array sequentially and acquiring the corresponding images that contain different spatial frequency components, high spatial resolution and quantitative phase imaging can be achieved in the case of large field-of-view. Nevertheless, FPM has high requirements for the system construction and data acquisition processes, such as precise LEDs position, accurate focusing and appropriate exposure time, which brings many limitations to its practical applications. In this paper, inspired by artificial neural network, we propose a Fourier ptychography multi-parameter neural network (FPMN) with composite physical prior optimization. A hybrid parameter determination strategy combining physical imaging model and data-driven network training is proposed to recover the multi layers of the network corresponding to different physical parameters, including sample complex function, system pupil function, defocus distance, LED array position deviation and illumination intensity fluctuation, etc. Among these parameters, LED array position deviation is recovered based on the features of brightfield to darkfield transition low-resolution images while the others are recovered in the process of training of the neural network. The feasibility and effectiveness of FPMN

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Single-shot phase contrast microscopy using polarisation-resolved differential phase contrast

Cited by 2 publications

References 10 publications

POLCAM: Instant molecular orientation microscopy for the life sciences

POLCAM: Instant molecular orientation microscopy for the life sciences

Fourier ptychography multi-parameter neural network with composite physical priori optimization

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