Toward a priori noise characterization for real-time edge-aware denoising in fluoroscopic devices

Abstract Background Low-dose X-ray images have become increasingly popular in the last decades, due to the need to guarantee the lowest reasonable patient’s exposure. Dose reduction causes a substantial increase of quantum noise, which needs to be suitably suppressed. In particular, real-time denoising is required to support common interventional fluoroscopy procedures. The knowledge of noise statistics provides precious information that helps to improve denoising performances, thus making noise estimation a crucial task for effective denoising strategies. Noise statistics depend on different factors, but are mainly influenced by the X-ray tube settings, which may vary even within the same procedure. This complicates real-time denoising, because noise estimation should be repeated after any changes in tube settings, which would be hardly feasible in practice. This work investigates the feasibility of an a priori characterization of noise for a single fluoroscopic device, which would obviate the need for inferring noise statics prior to each new images acquisition. The noise estimation algorithm used in this study was tested in silico to assess its accuracy and reliability. Then, real sequences were acquired by imaging two different X-ray phantoms via a commercial fluoroscopic device at various X-ray tube settings. Finally, noise estimation was performed to assess the matching of noise statistics inferred from two different sequences, acquired independently in the same operating conditions. Results The noise estimation algorithm proved capable of retrieving noise statistics, regardless of the particular imaged scene, also achieving good results even by using only 10 frames (mean percentage error lower than 2%). The tests performed on the real fluoroscopic sequences confirmed that the estimated noise statistics are independent of the particular informational content of the scene from which they have been inferred, as they turned out to be consistent in sequences of the two different phantoms acquired independently with the same X-ray tube settings. Conclusions The encouraging results suggest that an a priori characterization of noise for a single fluoroscopic device is feasible and could improve the actual implementation of real-time denoising strategies that take advantage of noise statistics to improve the trade-off between noise reduction and details preservation.

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A Characterization of the Phase Transitions in Saturated Monogalactosyldiacylglycerol-Water Systems Using Real-Time X-Ray Diffraction Methods

Molecular Crystals and Liquid Crystals Incorporating Nonlinear Optics ◽

10.1080/00268948908037167 ◽

1989 ◽

Vol 167 (1) ◽

pp. 109-121

Author(s):

P. J. Quinn ◽

L. J. Lis

Keyword(s):

Phase Transitions ◽

Real Time ◽

Water Systems ◽

X Ray Diffraction ◽

X Ray

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A New Online Dynamic Testing Method for Noise of Broadcast Transmitter

Wireless Communications and Mobile Computing ◽

10.1155/2020/3867913 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Shan-Shan Li ◽

Jian Zhou ◽

Xuan Wang

Keyword(s):

Real Time ◽

Data Storage ◽

Dynamic Testing ◽

Noise Figure ◽

Estimation Algorithm ◽

Test Method ◽

Noise Estimation ◽

Experimental Simulation ◽

Spectrum Estimation ◽

Low Efficiency

Aiming at the shortcomings of traditional broadcast transmitter noise test methods, such as low efficiency, inconvenient data storage, and high requirements for testers, a dynamic online test method for transmitter noise is proposed. The principle of system composition and test method is given. The transmitter noise is real-time changing. The Voice Active Detection (VAD) noise estimation algorithm cannot track the transmitter noise change in real time. This paper proposes a combined noise estimation algorithm for VAD and dynamic estimation. By setting the threshold of the double-threshold VAD detection to be low, it can accurately detect the silent segment. The silent segment is used as a noise signal for noise estimation. For the nonsilent segment detected by the VAD, a minimum value search dynamic spectrum estimation algorithm based on the existence probability of the speech (IMCRA) is used for noise estimation. Transmitter noise is measured by calculating the noise figure (NF).The test method collects the input and output data of the transmitter in real time, which has better accuracy and real-time performance, and the feasibility of the method is verified by experimental simulation.

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Energy-based binary segmentation of snow microtomographic images

Journal of Glaciology ◽

10.3189/2013jog13j035 ◽

2013 ◽

Vol 59 (217) ◽

pp. 859-873 ◽

Cited By ~ 24

Author(s):

Pascal Hagenmuller ◽

Guillaume Chambon ◽

Bernard Lesaffre ◽

Frédéric Flin ◽

Mohamed Naaim

Keyword(s):

Spatial Information ◽

A Priori ◽

Synthetic Image ◽

X Ray ◽

Require Time ◽

Segmentation Methods ◽

Binary Segmentation ◽

Data Fidelity ◽

Local Spatial Information

AbstractX-ray microtomography has become an essential tool for investigating the mechanical and physical properties of snow, which are tied to its microstructure. To allow a quantitative characterization of the microstructure, the grayscale X-ray attenuation coefficient image has to be segmented into a binary ice/pore image. This step, called binary segmentation, is crucial and affects all subsequent analysis and modeling. Common segmentation methods are based on thresholding. In practice, these methods present some drawbacks and often require time-consuming manual post-processing. Here we present a binary segmentation algorithm based on the minimization of a segmentation energy. This energy is composed of a data fidelity term and a regularization term penalizing large interface area, which is of particular interest for snow where sintering naturally tends to reduce the surface energy. The accuracy of the method is demonstrated on a synthetic image. The method is then successfully applied on microtomographic images of snow and compared to the threshold-based segmentation. The main advantage of the presented approach is that it benefits from local spatial information. Moreover, the effective resolution of the segmented image is clearly defined and can be chosen a priori.

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X-ray Spectroscopy and Chemometric Methods for Real-Time Characterization of Petroleum for the Refining Process through True Boiling Point Curve and American Petroleum Institute Gravity

Energy & Fuels ◽

10.1021/ef400230m ◽

2013 ◽

Vol 27 (6) ◽

pp. 3014-3021 ◽

Cited By ~ 4

Author(s):

Claudete Bernardo Henriques ◽

Julio Cesar Laurentino Alves ◽

Ronei Jesus Poppi ◽

Rubens Maciel Filho ◽

Maria Izabel Maretti Silveira Bueno

Keyword(s):

Real Time ◽

Boiling Point ◽

American Petroleum Institute ◽

Refining Process ◽

Chemometric Methods ◽

X Ray ◽

Point Curve

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X-Ray Characterization of Real Fuel Sprays for Gasoline Direct Injection

ASME 2020 Internal Combustion Engine Division Fall Technical Conference ◽

10.1115/icef2020-2974 ◽

2020 ◽

Author(s):

Brandon A. Sforzo ◽

Aniket Tekawade ◽

Alan L. Kastengren ◽

Kamel Fezzaa ◽

Jan Ilavsky ◽

...

Keyword(s):

Mass Distribution ◽

Direct Injection ◽

Diagnostic Techniques ◽

Operating Conditions ◽

Gasoline Direct Injection ◽

Fuel Blend ◽

Fuel Mass ◽

X Ray ◽

Fuel Blends

Abstract The effects of fuel blend properties on spray and injector performance has been investigated for several operating conditions in a side-mount injector for Gasoline Direct Injection (GDI) using two certification fuel blends, Euro 5 and Euro 6. Several X-ray diagnostic techniques were conducted to characterize the injector and spray morphology. Detailed internal geometry of the GDI injector was measured with a feature-resolution of 1.8 micrometers, through the use of hard X-ray tomography. The geometry characterization of this six-hole GDI, side mount injector, quantifies relevant hole and counterbore dimensions and reveals the intricate details within the flow passages, including surface roughness and micron-sized features. Internal valve motion was measured with a temporal resolution of 20 microseconds and a spatial resolution of 2.0 micrometers, for three injection pressures and several injector energizing strategies. The needle motion for both fuels exhibit similar lift profiles for common energizing commands. A combination of X-ray radiography and Ultra-Small-Angle X-ray Scattering (USAXS) was used to characterize the fuel mass distribution and the droplet sizing, respectively. Tomographic spray radiography revealed the near-nozzle distribution of fuel mass for each of the fuels, and the asymmetry produced by the angled nozzles. Under evaporative conditions, the two fuels show minor differences in peak fuel mass distribution during steady injection, though both exhibit fluctuations in injection during the early, transient phase. US-AXS measurements of the path-specific surface area of the spray indicated lower peak values for the more evaporative conditions in the near nozzle region. These spray measurements portray the specific behavior of real fuel blends under a variety of conditions, illustrating the need to examine multi-component fuels to better understand relevant cases. Furthermore, this work furnishes the realistic boundary values for simulations to appropriately predict the sprays which were experimentally measured, and influenced by those realistic conditions.

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Characterization of a Lignite Ash from the Metc Gasifier I. Mineralogy

MRS Proceedings ◽

10.1557/proc-43-165 ◽

1984 ◽

Vol 43 ◽

Cited By ~ 1

Author(s):

Gregory J. McCarthy ◽

Lindsay P. Keller ◽

Robert J. Stevenson ◽

Kevin C. Galbreath ◽

Aaron L. Steinwand

Keyword(s):

Microprobe Analysis ◽

Electron Microprobe Analysis ◽

Operating Conditions ◽

X Ray Diffraction ◽

Detailed Characterization ◽

X Ray ◽

Large Numbers ◽

Inorganic Constituents ◽

Micrometer Scale

AbstractUtilization or disposal of gasification ash requires detailed characterization of its chemistry and phase formation (mineralogy). A North Dakota lignite ash produced in the Morgantown Energy Technology Center (METC) gasifier has been studied in detail by x-ray diffraction and electron microprobe analysis. The ash was coarse (84% of grains larger than 1.0 mm) but a typical grain was composed of a dozen or more crystalline phases with dimensions on the micrometer scale as well as less abundant glass phases. Hard centimeter-size clinkers suggested partial melting followed by crystallization. Silicates (dicalcium silicates (C2S), merwinite, Ca-Na-silicate (CNS), quartz), aluminosilicates (melilite, nepheline, carnegieite), oxides (ferrite spinels, periclase, hematite), calcite and minor zeolites comprised the dominant mineralogy. Microprobe analyses were obtained for large numbers of grains of the C2S phases, CNS, merwinite, melilite, ferrite spinels and calcite. The remaining phases had crystal sizes too small for analysis. A model is proposed for the genesis of this ash based on the inorganic constituents of lignite and the gasifier operating conditions.

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Real-time algorithm for Poissonian noise reduction in low-dose fluoroscopy: performance evaluation

BioMedical Engineering OnLine ◽

10.1186/s12938-019-0713-7 ◽

2019 ◽

Vol 18 (1) ◽

Cited By ~ 3

Author(s):

A. Sarno ◽

E. Andreozzi ◽

D. De Caro ◽

G. Di Meo ◽

A. G. M. Strollo ◽

...

Keyword(s):

Image Quality ◽

Real Time ◽

Video Processing ◽

Moving Objects ◽

Quantum Noise ◽

Moving Average ◽

Threshold Level ◽

Computational Time ◽

X Ray ◽

Mask Size

Abstract Background Quantum noise intrinsically limits the quality of fluoroscopic images. The lower is the X-ray dose the higher is the noise. Fluoroscopy video processing can enhance image quality and allows further patient’s dose lowering. This study aims to assess the performances achieved by a Noise Variance Conditioned Average (NVCA) spatio-temporal filter for real-time denoising of fluoroscopic sequences. The filter is specifically designed for quantum noise suppression and edge preservation. It is an average filter that excludes neighborhood pixel values exceeding noise statistic limits, by means of a threshold which depends on the local noise standard deviation, to preserve the image spatial resolution. The performances were evaluated in terms of contrast-to-noise-ratio (CNR) increment, image blurring (full width of the half maximum of the line spread function) and computational time. The NVCA filter performances were compared to those achieved by simple moving average filters and the state-of-the-art video denoising block matching-4D (VBM4D) algorithm. The influence of the NVCA filter size and threshold on the final image quality was evaluated too. Results For NVCA filter mask size of 5 × 5 × 5 pixels (the third dimension represents the temporal extent of the filter) and a threshold level equal to 2 times the local noise standard deviation, the NVCA filter achieved a 10% increase of the CNR with respect to the unfiltered sequence, while the VBM4D achieved a 14% increase. In the case of NVCA, the edge blurring did not depend on the speed of the moving objects; on the other hand, the spatial resolution worsened of about 2.2 times by doubling the objects speed with VBM4D. The NVCA mask size and the local noise-threshold level are critical for final image quality. The computational time of the NVCA filter was found to be just few percentages of that required for the VBM4D filter. Conclusions The NVCA filter obtained a better image quality compared to simple moving average filters, and a lower but comparable quality when compared with the VBM4D filter. The NVCA filter showed to preserve edge sharpness, in particular in the case of moving objects (performing even better than VBM4D). The simplicity of the NVCA filter and its low computational burden make this filter suitable for real-time video processing and its hardware implementation is ready to be included in future fluoroscopy devices, offering further lowering of patient’s X-ray dose.

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Characterization of occurence and distribution of invisible gold in ore by EPMA

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100134831 ◽

1990 ◽

Vol 48 (2) ◽

pp. 246-247

Author(s):

Shuihe Mao

Keyword(s):

Beam Current ◽

Operating Conditions ◽

Beam Diameter ◽

Invisible Gold ◽

X Ray ◽

Space Resolution ◽

High Space ◽

Main Component ◽

Order Line

Owing to the invisibility of ultramicron gold (invisible gold) in “Carlin type” gold ore, it is extremely difficult to investigate its occurrence and distribution by conventional determinative means.EPMA has been proved to be very powerful instrument for doing research on this subject because it has advantages of high space resolution, nondestructive,getting quantitative analysis results and observing various kinds of images continuously with same equipment etc.The unoxidized ore sample is selected from drill cuttings at a “Carl in type” gold mine in Southwest China with gold tenor of 31.02 g/t and weighs 2438g. The operating conditions of EPMA are: accelerating voltage 25kV, beam current 1×10-8 A, beam diameter about 1 μm. AuLα but not AuMα is preferably chosen as analysed x-ray line, because AuMα1 (5.840A) is overlapping with the 3rd order line of FeKα (5.812A) to some extent and iron is the main component of pyrite matrix. According to the expression of detection limit(CDL ), the calculated value of CDL under the circumstances is 0.038%.

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