Apparatus and fast method for cancer cell classification based on high harmonic coherent diffraction imaging in reflection geometry

2014 ◽  
Author(s):  
Michael Zürch ◽  
Stefan Foertsch ◽  
Mark Matzas ◽  
Katharina Pachmann ◽  
Rainer Kuth ◽  
...  
2014 ◽  
Vol 1 (3) ◽  
pp. 031008 ◽  
Author(s):  
Michael Zürch ◽  
Stefan Foertsch ◽  
Mark Matzas ◽  
Katharina Pachmann ◽  
Rainer Kuth ◽  
...  

2012 ◽  
Author(s):  
Matthew D. Seaberg ◽  
Daniel E. Adams ◽  
Bosheng Zhang ◽  
Dennis F. Gardner ◽  
Margaret M. Murnane ◽  
...  

2013 ◽  
Vol 46 (2) ◽  
pp. 312-318 ◽  
Author(s):  
Jose A. Rodriguez ◽  
Rui Xu ◽  
Chien-Chun Chen ◽  
Yunfei Zou ◽  
Jianwei Miao

Coherent diffraction imaging (CDI) is high-resolution lensless microscopy that has been applied to image a wide range of specimens using synchrotron radiation, X-ray free-electron lasers, high harmonic generation, soft X-ray lasers and electrons. Despite recent rapid advances, it remains a challenge to reconstruct fine features in weakly scattering objects such as biological specimens from noisy data. Here an effective iterative algorithm, termed oversampling smoothness (OSS), for phase retrieval of noisy diffraction intensities is presented. OSS exploits the correlation information among the pixels or voxels in the region outside of a support in real space. By properly applying spatial frequency filters to the pixels or voxels outside the support at different stages of the iterative process (i.e.a smoothness constraint), OSS finds a balance between the hybrid input–output (HIO) and error reduction (ER) algorithms to search for a global minimum in solution space, while reducing the oscillations in the reconstruction. Both numerical simulations with Poisson noise and experimental data from a biological cell indicate that OSS consistently outperforms the HIO, ER–HIO and noise robust (NR)–HIO algorithms at all noise levels in terms of accuracy and consistency of the reconstructions. It is expected that OSS will find application in the rapidly growing CDI field, as well as other disciplines where phase retrieval from noisy Fourier magnitudes is needed. TheMATLAB(The MathWorks Inc., Natick, MA, USA) source code of the OSS algorithm is freely available from http://www.physics.ucla.edu/research/imaging.


2013 ◽  
Vol 21 (18) ◽  
pp. 21131 ◽  
Author(s):  
Michael Zürch ◽  
Christian Kern ◽  
Christian Spielmann

Nano Letters ◽  
2021 ◽  
Author(s):  
Tomoya Kawaguchi ◽  
Vladimir Komanicky ◽  
Vitalii Latyshev ◽  
Wonsuk Cha ◽  
Evan R. Maxey ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rujia Li ◽  
Liangcai Cao

AbstractPhase retrieval seeks to reconstruct the phase from the measured intensity, which is an ill-posed problem. A phase retrieval problem can be solved with physical constraints by modulating the investigated complex wavefront. Orbital angular momentum has been recently employed as a type of reliable modulation. The topological charge l is robust during propagation when there is atmospheric turbulence. In this work, topological modulation is used to solve the phase retrieval problem. Topological modulation offers an effective dynamic range of intensity constraints for reconstruction. The maximum intensity value of the spectrum is reduced by a factor of 173 under topological modulation when l is 50. The phase is iteratively reconstructed without a priori knowledge. The stagnation problem during the iteration can be avoided using multiple topological modulations.


2021 ◽  
Vol 103 (21) ◽  
Author(s):  
Matthew J. Wilkin ◽  
Siddharth Maddali ◽  
Stephan O. Hruszkewycz ◽  
Anastasios Pateras ◽  
Richard L. Sandberg ◽  
...  

2021 ◽  
Vol 140 ◽  
pp. 106530
Author(s):  
Yuanyuan Liu ◽  
Qingwen Liu ◽  
You Li ◽  
Junyong Zhang ◽  
Zuyuan He

2011 ◽  
Author(s):  
Jonathan Potier ◽  
Sebastien Fricker ◽  
Mourad Idir

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