Two-Axis Isotropic Differential Phase Contrast Transfer Function Using Gradient Amplitude Modulation For Phase Imaging

2017 ◽  
Author(s):  
Hsi-Hsun Chen ◽  
Yuan Luo
Keyword(s):  
Transfer Function ◽  
Amplitude Modulation ◽  
Phase Contrast ◽  
Phase Imaging ◽  
Contrast Transfer Function ◽  
Differential Phase ◽  
Differential Phase Contrast ◽  
Gradient Amplitude

scholarly journals Integrated Differential Phase Contrast (iDPC)–Direct Phase Imaging in STEM for Thin Samples

2016 ◽  
Vol 22 (S3) ◽  
pp. 36-37 ◽  
Author(s):  
Ivan Lazic ◽  
Eric G.T. Bosch ◽  
Sorin Lazar ◽  
Maarten Wirix ◽  
Emrah Yücelen
Keyword(s):  
Phase Contrast ◽  
Phase Imaging ◽  
Differential Phase ◽  
Differential Phase Contrast ◽  
Thin Samples

scholarly journals Quantitative electric field mapping in thin specimens using a segmented detector: Revisiting the transfer function for differential phase contrast

2017 ◽  
Vol 182 ◽  
pp. 258-263 ◽  
Author(s):  
Takehito Seki ◽  
Gabriel Sánchez-Santolino ◽  
Ryo Ishikawa ◽  
Scott D. Findlay ◽  
Yuichi Ikuhara ◽  
...  
Keyword(s):  
Transfer Function ◽  
Electric Field ◽  
Phase Contrast ◽  
Field Mapping ◽  
Differential Phase ◽  
Segmented Detector ◽  
Differential Phase Contrast

Isotropic quantitative differential phase contrast imaging techniques: a review

2021 ◽  
Author(s):  
Sunil Vyas ◽  
An-Cin Li ◽  
Yu-Hsiang Lin ◽  
J Andrew Yeh ◽  
Yuan Luo
Keyword(s):  
Deep Learning ◽  
Transfer Function ◽  
Phase Contrast ◽  
Phase Contrast Imaging ◽  
Isotropic Phase ◽  
Learning Approach ◽  
Contrast Imaging ◽  
Quantitative Phase ◽  
Differential Phase ◽  
Differential Phase Contrast

Abstract Optical phase shifts generated by the spatial variation of refractive index and thickness inside the transparent samples can be determined by intensity measurements through quantitative phase contrast imaging. In this review, we focus on isotropic quantitative differential phase-contrast microscopy(qDPC), which is a non-interferometric quantitative phase imaging technique and belongs to the class of deterministic phase retrieval from intensity. The qDPC is based on the principle of a weak object transfer function together with the first-order Born approximation in a partially coherent illumination system and wide-field detection, which offers multiple advantages. We review basic principles, imaging systems, and demonstrate examples of differential phase contrast (DPC) imaging for biomedical applications. In addition to the previous work, we present the latest results for isotropic phase contrast enhancements using a deep learning approach. We implemented a supervised learning approach with the U-Net model to reduce the number of measurements required for multi-axis measurements associated with the isotropic phase transfer function. We show that a well-designed and trained neural network provide a fast and efficient way to predict quantitative phase maps for live cells, which can help in determining morphological parameters. The prospects of deep learning in quantitative phase microscopy, particularly for isotropic quantitative phase estimation, are discussed.

The role of differential phase contrast in electron microscopy

1978 ◽  
Vol 36 (1) ◽  
pp. 176-177
Author(s):  
E.M. Waddell ◽  
J.N. Chapman ◽  
R.P. Ferrier
Keyword(s):  
Phase Contrast ◽  
Practical Method ◽  
Position Vector ◽  
Differential Phase ◽  
Pure Phase ◽  
Differential Phase Contrast ◽  
The Difference ◽  
Image Position ◽  
First Moment

Dekkers and de Lang (1977) have discussed a practical method of realising differential phase contrast in a STEM. The method involves taking the difference signal from two semi-circular detectors placed symmetrically about the optic axis and subtending the same angle (2α) at the specimen as that of the cone of illumination. Such a system, or an obvious generalisation of it, namely a quadrant detector, has the characteristic of responding to the gradient of the phase of the specimen transmittance. In this paper we shall compare the performance of this type of system with that of a first moment detector (Waddell et al.1977).For a first moment detector the response function R(k) is of the form R(k) = ck where c is a constant, k is a position vector in the detector plane and the vector nature of R(k)indicates that two signals are produced. This type of system would produce an image signal given bywhere the specimen transmittance is given by a (r) exp (iϕ (r), r is a position vector in object space, ro the position of the probe, ⊛ represents a convolution integral and it has been assumed that we have a coherent probe, with a complex disturbance of the form b(r-ro) exp (iζ (r-ro)). Thus the image signal for a pure phase object imaged in a STEM using a first moment detector is b2 ⊛ ▽ø. Note that this puts no restrictions on the magnitude of the variation of the phase function, but does assume an infinite detector.

Evaluation method for imaging plate resolution by means of phase contrast transfer function

1995 ◽  
Vol 53 ◽  
pp. 662-663 ◽  
Author(s):  
T. Oikawa ◽  
H. Kosugi ◽  
F. Hosokawa ◽  
D. Shindo ◽  
M. Kersker
Keyword(s):  
Transfer Function ◽  
Phase Contrast ◽  
Evaluation Method ◽  
Amorphous Film ◽  
Imaging Plate ◽  
X Rays ◽  
Special Shape ◽  
Contrast Transfer Function ◽  
Contrast Image ◽  
Specimen Shape

Evaluation of the resolution of the Imaging Plate (IP) has been attempted by some methods. An evaluation method for IP resolution, which is not influenced by hard X-rays at higher accelerating voltages, was proposed previously by the present authors. This method, however, requires truoblesome experimental preperations partly because specially synthesized hematite was used as a specimen, and partly because a special shape of the specimen was used as a standard image. In this paper, a convenient evaluation method which is not infuenced by the specimen shape and image direction, is newly proposed. In this method, phase contrast images of thin amorphous film are used.Several diffraction rings are obtained by the Fourier transformation of a phase contrast image of thin amorphous film, taken at a large under focus. The rings show the spatial-frequency spectrum corresponding to the phase contrast transfer function (PCTF). The envelope function is obtained by connecting the peak intensities of the rings. The evelope function is offten used for evaluation of the instrument, because the function shows the performance of the electron microscope (EM).

Correction of the contrast transfer function to determine the radial density distribution of frozen-hydrated tobacco mosaic virus

1992 ◽  
Vol 50 (1) ◽  
pp. 536-537
Author(s):  
Michael F. Smith ◽  
John P. Langmore
Keyword(s):  
Transfer Function ◽  
Phase Contrast ◽  
Heavy Atom ◽  
Biological Molecules ◽  
Frequency Compensation ◽  
Contrast Transfer Function ◽  
High Background ◽  
Low Contrast ◽  
Radial Density Distribution ◽  
Excellent Preservation

The purpose of image reconstruction is to determine the mass densities within molecules by analysis of the intensities within images. Cryo-EM offers this possibility by virtue of the excellent preservation of internal structure without heavy atom staining. Cryo-EM images, however, have low contrast because of the similarity between the density of biological material and the density of vitreous ice. The images also contain a high background of inelastic scattering. To overcome the low signal and high background, cryo-images are typically recorded 1-3 μm underfocus to maximize phase contrast. Under those conditions the image intensities bear little resemblance to the object, due to the dependence of the contrast transfer function (CTF) upon spatial frequency. Compensation (i.e., correction) for the CTF is theoretically possible, but implementation has been rare. Despite numerous studies of molecules in ice, there has never been a quantitative evaluation of compensated images of biological molecules of known structure.

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