Single‐Shot Optical Anisotropy Imaging with Quantitative Polarization Interference Microscopy

Ge, Baoliang; Zhou, Renjie; Takiguchi, Yuichi; Yaqoob, Zahid; So, Peter T. C.

doi:10.1002/lpor.201800070

Cited by 15 publications

(10 citation statements)

References 48 publications

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“…Recent advances in computational microscopy show that robust retrieval of phase from throughfocus series is possible via weak object transfer function model of image formation (14)(15)(16)(17)(18)(19). Polarization can be converted into intensity modulation using optical components that selectively transmit and change polarization (20)(21)(22). Quantitative imaging of structural anisotropy has been demonstrated by probing the specimen with complementary polarization states of light, which we have achieved with liquid-crystal based PolScope (LC-PolScope) (20,23,24).…”

Section: Introductionmentioning

confidence: 99%

“…Polarization microscopes measure retardance 1 , i.e., orientation-dependent optical path length, which is modulated by the structural anisotropy below the spatial diffraction limit and has been used to make measurements well below the resolution limit (23). Structural anisotropy can be measured using tunable polarization modulators in the illumination or the detection path of the microscope (24)(25)(26)(27)(28). Shribak et al (13) developed a method that employed multiple liquid crystal modulators for joint analysis of phase and retardance in 2D, but not in 3D live specimens.…”

Section: Introductionmentioning

confidence: 99%

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Revealing architectural order with quantitative label-free imaging and deep learning

Guo

Krishnan

Folkesson

et al. 2019

Preprint

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Methods for imaging architecture of biological systems are currently not as scalable as genomic, transcriptomic, or proteomic technologies, because they rely on labels instead of intrinsic signatures. Label-free visualization of diverse biological structures is feasible with phase and polarization of light. However, distinguishing structures from information-dense label-free images is challenging. Recent advances in deep learning can distinguish structures from label-free images based on their shape. Here, we report joint use of polarization resolved imaging, reconstruction of optical properties, and deep neural networks for scalable analysis of complex structures. We reconstruct quantitative three-dimensional density, anisotropy, and orientation from polarization-and depthresolved images. We report a computationally efficient variant of U-Net architecture to predict 3D fluorescent structure from its density, anisotropy, and orientation. We evaluate the performance of our models by predicting anisotropic F-actin and isotropic nuclei. We report label-free prediction of myelination in human brain tissue sections and demonstrate the model's ability to rescue inconsistent labeling. We anticipate that the proposed approach will enable quantitative analysis of architectural order across scales of organelles to tissues. Label-free Microscopy | Polarization | Phase | Computational Imaging | Deep Learning Guo, Yeh, Folkesson et al. | bioRχiv | November 18, 2019 | 1-26 Guo, Yeh, Folkesson et al. | Learning architectural order bioRχiv | 3

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Revealing architectural order with quantitative label-free imaging and deep learning

Guo

Krishnan

Folkesson

et al. 2019

Preprint

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“…Scalar scattering potential is a scaled difference of the refractive indices of the specimen B Characterization of spatial resolution and accuracy and the surrounding medium, which is a key concept employed in the diffraction tomography of 3D refractive index (density of bound electrons) (38). An extension of scattering potential, 2 × 2 scattering potential tensor, has been developed (29,39) for volumetric reconstruction of projected anisotropy. Our work generalizes the formulation to measure a more complete 3 × 3 scattering potential tensor, which allows reconstruction of volumetric distribution of density, 3D anisotropy, and material symmetry.…”

Section: Reconstruction Of Uptmentioning

confidence: 99%

“…A key limitation of current polarized light microscopy (28,29,39) approaches has been that their light paths are not sensitive to the inclination of the 3D anisotropy. As a result, they report anisotropy projected on the microscope's image plane.…”

Section: C: Upti Enables Multi-scale Analysis Of the Architecture Of Mouse Brain Tissuementioning

confidence: 99%

uPTI: uniaxial permittivity tensor imaging of intrinsic density and anisotropy

Yeh

Ivanov

Guo

et al. 2020

Preprint

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Architecture of biological systems is important for their homeostatic functions and is predictive of pathology. Volumetric imaging of intrinsic density, anisotropy, and 3D orientation of cell and tissue components is informative, but still challenging. These physical properties can be described succinctly by the volumetric distribution of the specimen’s permittivity tensor (PT). We report uniaxial permittivity tensor imaging (uPTI), a novel approach for label-free volumetric imaging with diffraction-limited resolution. uPTI combines the oblique illumination and the polarization imaging with high numerical apertures to encode the specimen’s permittivity tensor into intensity modulations, which are decoded with a novel vector diffraction model and a multi-channel convex optimization. The uPTI volumes of polystyrene beads and laser-fabricated anisotropic glass targets show that 3D uPT measurements are quantitative, with diffraction-limited spatial resolution of 0.23 × 0.23 × 0.8 μm3. Automated 2D and 3D imaging of a mouse brain section reveals anatomy at multiple scales (cm – 250 nm) and demonstrates that uPTI enables analysis of the density, anisotropy, and orientation of axon bundles and single axons. We multiplex uPTI with fluorescence de-convolution microscopy to enable correlative analysis of physical and molecular architecture of iPSC-derived cardiomyocytes. uPTI can be added to an existing widefield microscope as a low cost module. We share our implementation of the forward model and optimization algorithms via open source repository. Collectively, the reported advances in optical design, image formation, reconstruction algorithms, and biological interpretation open multiple avenues to study architecture of organelles, cells and tissue sections, including human cells and tissues that are challenging to label.

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“…Incorporating off-axis QPI into polarization light microscopy allows one to reduce the number of measurements for quantitative retrieval of polarization parameters 6,[27][28][29] , but these approaches still require multiple measurements. We had first overcome this limitation in a single-shot quantitative polarization imaging technique utilizing shearing interferometry and a novel retrieval algorithm 30 . However, the Wollaston prism used in this system severely limits the image field-of-view (FOV) to a narrow rectangle.…”

Section: Introductionmentioning

confidence: 99%

Single-Shot Quantitative Polarization Imaging of Complex Birefringent Structure Dynamics

Zhang

et al. 2021

ACS Photonics

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Polarization light microscopes are powerful tools for probing molecular order and orientation in birefringent materials. While a multitude of polarization light microscopy techniques are often used to access steadystate properties of birefringent samples, quantitative measurements of the molecular orientation dynamics on the millisecond time scale have remained a challenge. We propose polarized shearing interference microscopy (PSIM), a single-shot quantitative polarization imaging method, for extracting the retardance and orientation angle of the laser beam transmitting through optically anisotropic specimens with complex structures. The measurement accuracy and imaging performances of PSIM are validated by imaging a rotating wave plate and a bovine tendon specimen. We demonstrate that PSIM can quantify the dynamics of a flowing lyotropic chromonic liquid crystal in a microfluidic channel at an imaging speed of 506 frames per second (only limited by the camera frame rate), with a field-of-view of up to 350×350 μm 2 and a diffraction-limit spatial resolution of ∼2 μm. We envision that PSIM will find a broad range of applications in quantitative material characterization under dynamical conditions.

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Single‐Shot Optical Anisotropy Imaging with Quantitative Polarization Interference Microscopy

Cited by 15 publications

References 48 publications

Revealing architectural order with quantitative label-free imaging and deep learning

Revealing architectural order with quantitative label-free imaging and deep learning

uPTI: uniaxial permittivity tensor imaging of intrinsic density and anisotropy

Single-Shot Quantitative Polarization Imaging of Complex Birefringent Structure Dynamics

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