The effect of digital unsharp-mask filtering on the signal-to-noise ratio in computed radiography

1991 ◽  
Vol 13 (3) ◽  
pp. 225-228 ◽  
Author(s):  
Risto H. Miettunen ◽  
Ossi A. Korhola
Keyword(s):  
Computed Radiography ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Unsharp Mask ◽  
Noise Ratio

scholarly journals Anode heel effect application with step wedge against effect of signal to noise ratio in computed radiography

2020 ◽  
Vol 4 (3) ◽  
pp. 75-82
Author(s):  
Ni Nyoman Ratini ◽  
I Made Yuliara ◽  
Windaryoto Windaryoto
Keyword(s):  
Computed Radiography ◽  
Signal To Noise Ratio ◽  
Pearson Correlation ◽  
P Value ◽  
Signal To Noise ◽  
Correlation Test ◽  
Pearson Correlation Test ◽  
R Value ◽  
Noise Ratio ◽  
Heel Effect

It was researched on the application of Anoda Heel Effect (AHE) with a step wedge on the effect of Signal To Noise Ratio (SNR) on Computed Radiography (CR) has been carried out. This research was conducted on a 21 step wedge with two treatments, namely the application of AHE and without the application of AHE. This measurement is repeated three times on radiographs to obtain a total image of six images (without the application of AHE as many as three images and with the application of AHE as many as three images). The results of taking radiographs using AHE and without AHE were measured using the RadiAnt Dicom Viewer program. The SNR value on the step wedge image without the AHE application has an average of 26.89. The SNR value on the step wedge image using AHE is 60.54. The results of the correlation test (Pearson correlation test) on the SNR showed that there was a significant and very strong effect of the application of AHE on the step wedge on the SNR in CR (p-value <0.001 and the R-value ranging from 0.600 to 0.799).

scholarly journals Analisis Jeda Waktu Pembacaan Imaging Plate Terhadap Signal to Noise Ratio pada Citra Computed Radiography

2015 ◽  
Vol 1 (2) ◽  
pp. 55-58
Author(s):  
Dwi Rochmayanti ◽  
Defia Ayusari ◽  
Andrey Nino Kurniawan
Keyword(s):  
Time Delay ◽  
Image Quality ◽  
Reading Time ◽  
Computed Radiography ◽  
Signal To Noise Ratio ◽  
Time Interval ◽  
Imaging Plate ◽  
Signal To Noise ◽  
Average Decrease ◽  
Noise Ratio

Backgroud: Imaging plate (IP) is a storage media on computed radiography (CR). IP that has been exposed and does not process immediately will decrease the latent image exponentially over time and degrade the image quality. Normally, 25% of signal will be lost if IP was scanned at 10 minutes till 8 hours after exposure. So It will decrease the image quality. Image quality is determined by several factors. One of them is the signal-to-noise ratio (SNR). This study aims to determine the effect of reading time delay of IP to SNR on CR image.Methods: This research was a quantitative study with an experimental approach. Population of this study was CR digital image with various time delay of IP reading. Samples were 51 digital images of water phantom read by IP reading with time interval was 0 hours, 0.5 hours, 1 hour; 1.5 hour, 2 hours, 2.5 hours, 3 hours, 3.5 hours, 4 hours, 4.5 hours, 5 hours, 5.5 hours, 6 hours, 6.5 hours, 7 hours, 7.5 hours and 8 hours after exposure. Image pixel value and noise was weasured by ImageJ software to determine the value of SNR, then analyzed statistically with the regression test.Results: There was effect of reading time delay to SNR on CR image. Time delay affected 30,5% decreasing of SNR. Generally, time delay of IP reading decrease the SNR. The average decrease was 1.55% of SNR.Conclusion: The decrease of the SNR value was not big enough, only 1.55%. However, it will better when IP read as soon as possible after exposure to reduce the decrease of image quality.

scholarly journals Faktor Eksposi terhadap Kualitas Citra Radiografi dan Dosis Pasien Menggunakan Parameter Penilaian Signal to Noise Ratio (SNR) pada Pemeriksaan Thorax Posteroanterior dengan Menggunakan Pesawat Computed Radiografi

2021 ◽  
Vol 7 (1) ◽  
pp. 15-18
Author(s):  
Surdiyah Asriningrum ◽  
Khaerul Ansory ◽  
Putra Tri Hasan
Keyword(s):  
Image Quality ◽  
Digital Image ◽  
Computed Radiography ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Measurement Results ◽  
Noise Ratio ◽  
Dose Radiation ◽  
Average Body

Background: The research was analyzing digital image quality and estimation dose patient by using  Signal to Noise Ratio (SNR) on Computed Radiography. SNR can be used for analyzing digital image spatial resolution and estimation dose accurately. The aims of this study to determine the influence of exposure factors on image quality and estimation dose patient.Methods: This type of research is a quantitative method with an experimental study. Direct experiments in August 2020 assessment with a sample of 9 adults posteroanterior chest photo with the average age of 20-50 years old with an average body weight of 50-69 kilograms. Results: The measurement results showed that the digital images will be analyzed by SNR, so it can be determined the optimum exposed factor of the highest SNR value and dose radiation. From the analysis, the highest SNR value at 121 kV, current 1 mAs, the lower dose radiation at 121 kV, current 0,9 mAs.Conclusions: There was an influence variation of an exposed factor on the quality of the image and dose to the patient.

Determination of the Best Emulsion for the Microscopy of Crystals

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.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

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.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

Speech Reception in the Presence of Classroom Noise

1979 ◽  
Vol 10 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Veronica Smyth
Keyword(s):  
Signal To Noise Ratio ◽  
Learning Processes ◽  
Speech Discrimination ◽  
Signal To Noise ◽  
Speech Reception ◽  
Monosyllabic Words ◽  
Noise Ratio

Three hundred children from five to 12 years of age were required to discriminate simple, familiar, monosyllabic words under two conditions: 1) quiet, and 2) in the presence of background classroom noise. Of the sample, 45.3% made errors in speech discrimination in the presence of background classroom noise. The effect was most marked in children younger than seven years six months. The results are discussed considering the signal-to-noise ratio and the possible effects of unwanted classroom noise on learning processes.

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