Tricky Registration for Unruly Data: Image Registration of Low-Signal-to-Noise Cryo-STEM Data

Functional 2-photon microscopy is a key technology for imaging neuronal activity which can, however, contain non-rigid movement artifacts. Despite the established performance of variational optical flow (OF) estimation in different computer vision areas and the importance of movement correction for 2-photon applications, no OF-based method for 2-photon imaging is available. We developed the easy-to-use toolbox Flow-Registration that outperforms previous alignment tools and allows to align and reconstruct even low signal-to-noise 2-photon imaging data.

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Enhancing the signal-to-noise ratio in ophthalmic optical coherence tomography by image registration—method and clinical examples

Journal of Biomedical Optics ◽

10.1117/1.2772879 ◽

2007 ◽

Vol 12 (4) ◽

pp. 041208 ◽

Cited By ~ 57

Author(s):

Thomas Martini Jo̸rgensen ◽

Jakob Thomadsen ◽

Ulrik Christensen ◽

Wael Soliman ◽

Birgit Sander

Keyword(s):

Optical Coherence Tomography ◽

Image Registration ◽

Signal To Noise Ratio ◽

Optical Coherence ◽

Signal To Noise ◽

Registration Method ◽

Noise Ratio

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Ultrasound Images Registration Based on Optimal Feature Descriptor Using Speeded Up Robust Feature

Iraqi Journal of Science ◽

10.24996/ijs.2020.61.9.26 ◽

2020 ◽

pp. 2395-2407

Author(s):

Hawra’a Lateef Joey ◽

Ahlam Hanoon Al-sudani ◽

Maher Faik Esmaile

Keyword(s):

Image Registration ◽

Execution Time ◽

Signal To Noise Ratio ◽

Objective Assessment ◽

Reference Image ◽

Feature Descriptor ◽

Ultrasound Images ◽

Signal To Noise ◽

The Us ◽

Noise Ratio

Image registration plays a significant role in the medical image processing field. This paper proposes a development on the accuracy and performance of the Speeded-Up Robust Surf (SURF) algorithm to create Extended Field of View (EFoV) Ultrasound (US) images through applying different matching measures. These measures include Euclidean distance, cityblock distance, variation, and correlation in the matching stage that was built in the SURF algorithm. The US image registration (fusion) was implemented depending on the control points obtained from the used matching measures. The matched points with higher frequency algorithm were proposed in this work to perform and enhance the EFoV for the US images, since the maximum accurate matching points would have been selected. The resulted fused images of these applied methods were evaluated subjectively and objectively. The objective assessment was conducted by calculating the execution time, peak signal to noise ratio (PSNR), and signal to noise ratio (SNR) of the registered images and the reference image which was fused manually by a physician. The results showed that the cityblock distance has the best result since it has the highest PSNR and SNR in addition to the lowest execution time.

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Image registration of low signal-to-noise cryo-STEM data

Ultramicroscopy ◽

10.1016/j.ultramic.2018.04.008 ◽

2018 ◽

Vol 191 ◽

pp. 56-65 ◽

Cited By ~ 27

Author(s):

Benjamin H. Savitzky ◽

Ismail El Baggari ◽

Colin B. Clement ◽

Emily Waite ◽

Berit H. Goodge ◽

...

Keyword(s):

Image Registration ◽

Signal To Noise

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Quantification of the accuracy limits of image registration using peak signal-to-noise ratio

Radiological Physics and Technology ◽

10.1007/s12194-016-0372-3 ◽

2016 ◽

Vol 10 (1) ◽

pp. 91-94 ◽

Cited By ~ 5

Author(s):

Yoshinori Tanabe ◽

Takayuki Ishida

Keyword(s):

Image Registration ◽

Signal To Noise Ratio ◽

Signal To Noise ◽

Noise Ratio

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A Novel Registration Algorithm for Pol-InSAR Images Based on the RVOG Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.198-199.1475 ◽

2012 ◽

Vol 198-199 ◽

pp. 1475-1480

Author(s):

Sha Sha Wu ◽

Dao Wei Yan ◽

Zheng Lu ◽

Ming Ming Bian

Keyword(s):

Image Registration ◽

Signal To Noise Ratio ◽

Synthetic Aperture ◽

Interferometric Synthetic Aperture Radar ◽

Estimation Result ◽

Coordinate Plane ◽

Signal To Noise ◽

Registration Algorithm ◽

Forested Areas ◽

Simulation Results

In the processing of the polarimetric interferometric synthetic aperture radar (Pol-InSAR), the image registration is a key procedure. If the error of image registration occurs, the signal-to-noise ratio (SNR) of the interferometric image will be lowered and the precision of the height estimation will be decreased. Numerous registration algorithms have been proposed to solve the above-mentioned problem. However, in forested areas, the effect of volume scattering is significant. This property yields the fact that the characteristic of phase and frequency in the interferometric image is not obvious, leading to the worse performance of conventional registration algorithms. In this paper, a novel registration algorithm based on the random volume over ground (RVOG) model is presented. The method employs the fact that the coherence coefficients of the same pixel are displayed as a beeline in the complex coordinate plane for forested scenes. The image offset which yields the best linearity of coherence coefficients will be treated as the final estimation result. Simulation results verify that this method is able to provide the image registration estimation in the pixel and sub-pixel levels.

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Radiation Damage, Contrast and Statistics in High Resolution Biological Electron Microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100068291 ◽

1970 ◽

Vol 28 ◽

pp. 260-261

Author(s):

Robert M. Glaeser

Keyword(s):

High Resolution ◽

Particle Flux ◽

Unit Area ◽

Signal To Noise ◽

Resolution Image ◽

High Resolution Image ◽

Pass Through ◽

Counting Statistics ◽

The Relationship ◽

Picture Element

It is well known that a large flux of electrons must pass through a specimen in order to obtain a high resolution image while a smaller particle flux is satisfactory for a low resolution image. The minimum particle flux that is required depends upon the contrast in the image and the signal-to-noise (S/N) ratio at which the data are considered acceptable. For a given S/N associated with statistical fluxtuations, the relationship between contrast and “counting statistics” is s131_eqn1, where C = contrast; r2 is the area of a picture element corresponding to the resolution, r; N is the number of electrons incident per unit area of the specimen; f is the fraction of electrons that contribute to formation of the image, relative to the total number of electrons incident upon the object.

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Determination of the Best Emulsion for the Microscopy of Crystals

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100096886 ◽

1981 ◽

Vol 39 ◽

pp. 32-33

Author(s):

David A. Grano ◽

Kenneth H. Downing

Keyword(s):

Spatial Frequency ◽

Information Transfer ◽

Signal To Noise Ratio ◽

Experimental Situation ◽

Photographic Emulsion ◽

Modulation Transfer ◽

Signal To Noise ◽

Frequency Space ◽

Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

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Experiments in Bright-Field Imaging with Hollow-Cone Illumination

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100097703 ◽

1981 ◽

Vol 39 ◽

pp. 226-227

Author(s):

W. Kunath ◽

K. Weiss ◽

E. Zeitler

Keyword(s):

Signal To Noise Ratio ◽

Carbon Support ◽

Electronic System ◽

Optic Axis ◽

Hollow Cone ◽

Signal To Noise ◽

Bright Field ◽

Noise Ratio ◽

Single Field ◽

Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

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