Reliable automatic alignment of tomographic projection data by passive auto-focus

2011 ◽  
Vol 38 (9) ◽  
pp. 4934-4945 ◽  
Author(s):  
A. Kingston ◽  
A. Sakellariou ◽  
T. Varslot ◽  
G. Myers ◽  
A. Sheppard
Keyword(s):  
Projection Data ◽  
Automatic Alignment ◽  
Auto Focus ◽  
Tomographic Projection

Registration of synthetic tomographic projection data sets using cross-correlation

1998 ◽  
Vol 43 (6) ◽  
pp. 1645-1657 ◽  
Author(s):  
E E Fitchard ◽  
J S Aldridge ◽  
P J Reckwerdt ◽  
T R Mackie
Keyword(s):  
Cross Correlation ◽  
Projection Data ◽  
Data Sets ◽  
Tomographic Projection

Computer Assisted Image Reconstruction of Oligomer Structure

1976 ◽  
Vol 34 ◽  
pp. 472-473
Author(s):  
A.M. Jones ◽  
A. Max Fiskin
Keyword(s):  
Three Dimensional ◽  
Depth Of Field ◽  
Computer Assisted ◽  
Projection Data ◽  
Two Dimensional ◽  
Single Particles ◽  
Dimensional Reconstruction ◽  
Computer Assisted Image ◽  
The Fourier Transform ◽  
Space Approach

If the tilt of a specimen can be varied either by the strategy of observing identical particles orientated randomly or by use of a eucentric goniometer stage, three dimensional reconstruction procedures are available (l). If the specimens, such as small protein aggregates, lack periodicity, direct space methods compete favorably in ease of implementation with reconstruction by the Fourier (transform) space approach (2). Regardless of method, reconstruction is possible because useful specimen thicknesses are always much less than the depth of field in an electron microscope. Thus electron images record the amount of stain in columns of the object normal to the recording plates. For single particles, practical considerations dictate that the specimen be tilted precisely about a single axis. In so doing a reconstructed image is achieved serially from two-dimensional sections which in turn are generated by a series of back-to-front lines of projection data.

Computer-Controlled Hrem Alignment Using Automated Diffractogram Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 532-533
Author(s):  
G.Y. Fan ◽  
O.L. Krivanek
Keyword(s):  
Electron Microscope ◽  
High Resolution ◽  
The Other ◽  
Full Information ◽  
Resolution Electron ◽  
Skilled Operator ◽  
Automatic Alignment ◽  
High Resolution Electron Microscope ◽  
Computer Controlled ◽  
Recorded Image

Full alignment of a high resolution electron microscope (HREM) requires five parameters to be optimized: the illumination angle (beam tilt) x and y, defocus, and astigmatism magnitude and orientation. Because neither voltage nor current centering lead to the correct illumination angle, all the adjustments must be done on the basis of observing contrast changes in a recorded image. The full alignment can be carried out by a computer which is connected to a suitable image pick-up device and is able to control the microscope, sometimes with greater precision and speed than even a skilled operator can achieve. Two approaches to computer-controlled (automatic) alignment have been investigated. The first is based on measuring the dependence of the overall contrast in the image of a thin amorphous specimen on the relevant parameters, the other on measuring the image shift. Here we report on our progress in developing a new method, which makes use of the full information contained in a computed diffractogram.

A Spectrum-Adaptive Decomposition Method for Effective Atomic Number Estimation Using Dual Energy CT

2020 ◽  
Vol 2020 (14) ◽  
pp. 293-1-293-7
Author(s):  
Ankit Manerikar ◽  
Fangda Li ◽  
Avinash C. Kak
Keyword(s):  
Atomic Number ◽  
Decomposition Method ◽  
Traditional Approach ◽  
Effective Atomic Number ◽  
Dual Energy ◽  
Performance Comparison ◽  
Estimation Methods ◽  
Dual Energy Ct ◽  
Projection Data ◽  
X Ray

Dual Energy Computed Tomography (DECT) is expected to become a significant tool for voxel-based detection of hazardous materials in airport baggage screening. The traditional approach to DECT imaging involves collecting the projection data using two different X-ray spectra and then decomposing the data thus collected into line integrals of two independent characterizations of the material properties. Typically, one of these characterizations involves the effective atomic number (Zeff) of the materials. However, with the X-ray spectral energies typically used for DECT imaging, the current best-practice approaches for dualenergy decomposition yield Zeff values whose accuracy range is limited to only a subset of the periodic-table elements, more specifically to (Z < 30). Although this estimation can be improved by using a system-independent ρe — Ze (SIRZ) space, the SIRZ transformation does not efficiently model the polychromatic nature of the X-ray spectra typically used in physical CT scanners. In this paper, we present a new decomposition method, AdaSIRZ, that corrects this shortcoming by adapting the SIRZ decomposition to the entire spectrum of an X-ray source. The method reformulates the X-ray attenuation equations as direct functions of (ρe, Ze) and solves for the coefficients using bounded nonlinear least-squares optimization. Performance comparison of AdaSIRZ with other Zeff estimation methods on different sets of real DECT images shows that AdaSIRZ provides a higher output accuracy for Zeff image reconstructions for a wider range of object materials.

Passive Auto-Focus Algorithm for Correcting Image Distortions Caused by Gas Flow in High-Temperature Measurements of Surface Phenomena

2012 ◽  
Vol 17 (4) ◽  
pp. 379-384 ◽  
Author(s):  
Krzysztof Strzecha ◽  
Tomasz Koszmider ◽  
Damian Zarębski ◽  
Wojciech Łobodziński
Keyword(s):  
High Temperature ◽  
Gas Flow ◽  
Temperature Measurements ◽  
Surface Phenomena ◽  
Auto Focus ◽  
High Temperature Measurements

Abstract In this paper, a case-study of the auto-focus algorithm for correcting image distortions caused by gas flow in high-temperature measurements of surface phenomena is presented. This article shows results of proposed algorithm and methods for increasing its accuracy.

scholarly journals CMIP5-Based Projection of Decadal and Seasonal Sea Surface Temperature Variations in East China Shelf Seas

2021 ◽  
Vol 9 (4) ◽  
pp. 367
Author(s):  
Huiqiang Lu ◽  
Chuan Xie ◽  
Cuicui Zhang ◽  
Jingsheng Zhai
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
The Yellow Sea ◽  
East China ◽  
Cmip5 Models ◽  
Projection Data ◽  
Observation Data ◽  
Model Intercomparison ◽  
Shelf Seas

The East China Shelf Seas, comprising the Bohai Sea, the Yellow Sea, and the shelf region of East China Sea, play significant roles among the shelf seas of the Western North Pacific Ocean. The projection of sea surface temperature (SST) changes in these regions is a hot research topic in marine science. However, this is a very difficult task due to the lack of available long-term projection data. Recently, with the high development of simulation technology based on numerical models, the model intercomparison projects, e.g., Phase 5 of the Climate Model Intercomparison Project (CMIP5), have become important ways of understanding climate changes. CMIP5 provides multiple models that can be used to estimate SST changes by 2100 under different representative concentration pathways (RCPs). This paper developed a CMIP5-based SST investigation framework for the projection of decadal and seasonal variation of SST in East China Shelf Seas by 2100. Since the simulation results of CMIP5 models may have degrees of errors, this paper uses hydrological observation data from World Ocean Atlas 2018 (WOA18) for model validation and correction. This paper selects seven representative ones including ACCESS1.3, CCSM4, FIO-ESM, CESM1-CAM5, CMCC-CMS, NorESM1-ME, and Max Planck Institute Earth System Model of medium resolution (MPI-ESM-MR). The decadal and seasonal SST changes in the next 100 years (2030, 2060, 2090) are investigated by comparing with the present analysis in 2010. The experimental results demonstrate that SST will increase significantly by 2100: the decadal SST will increase by about 1.55 °C, while the seasonal SST will increase by 1.03–1.95 °C.

scholarly journals Convolutional neural network as a tool for automatic alignment of electron optical beam shaping devices

2021 ◽  
Vol 27 (S1) ◽  
pp. 822-824
Author(s):  
Enzo Rotunno ◽  
Amir Tavabi ◽  
Paolo Rosi ◽  
Stefano Frabboni ◽  
Peter Tiemeijer ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Beam Shaping ◽  
Optical Beam ◽  
Automatic Alignment
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